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Events

The Taub Faculty of Computer Science Events and Talks

Discovering and Erasing Unsafe Concepts
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Niv Cohen
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Tuesday, 16.07.2024, 11:30
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Room 1061, Meyer Building
The rapid growth of generative models allows an ever-increasing variety of capabilities. Yet, these models may also produce undesired content suc...
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Hardware Sub-circuit Recognition via Subgraph Localization
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Dani Kogan
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Tuesday, 16.07.2024, 13:00
Hardware Reverse Engineering (HRE) involves gate-level Netlist extraction and specification discovery, wherein graph-based methods play a crucial role in identifying sub-circuits. We propose a novel approach for Subcircuit Recognition, essential for specification discovery in HRE, leveraging existing graph similarity kernels. Focusing on the reduced problem we formulate as Subgraph Localization, we delineate two key components: graph similarity metr...
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On the Algorithmic Foundations of Task Assistance Planning
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Eitan Bloch
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Wednesday, 17.07.2024, 09:30
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Zoom Lecture: 98269146871 & Computational Robotics Lab (CRL), 1st floor, Taub building
In this work we introduce the problem of task assistance planning where we are given two robots Rtask and Rassist. The first robot, Rtask, is in charge of performing a given task by executing a precomputed path. The second robot, Rassist, is in charge of assisting the task performed by Rtask using on-board sensors. The ability of Rassist to provide assistance to Rtask depends on the locations of both robots. Since Rtask is moving along its path, Rassist may also need to move to pr...
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Improved Approximations for Vector Bin Packing via Iterative Randomized Rounding
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Ariel Kulik
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Wednesday, 17.07.2024, 13:00
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Amado 814

The talk will focus on the d-dimensional vector bin packing problem. The input for the problem is a set of items, each associated with a d-dimensional weight vector. The objective is to partition the items into a minimal number of bins, such that the total weight of items in a bin is at most one in every dimension. The problem...
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Green AI
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Roy Schwartz (HUJI)
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Tuesday, 30.07.2024, 14:30
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Taub 337
The computations required for deep learning research have been doubling every few months, resulting in an estimated 5,000x increase from 2018 to 2022. This trend has led to unprecedented success in a range of AI tasks. In this talk I will discuss a few troubling side-effects of this trend, touching on issues of lack of inclusiveness within the research community, and an increasingly large environmental footprint. I will then present Green AI – an ...
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Statistically dense intervals in binary sequences with applications to assessing local enrichment in the human genome
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Shahar Mor
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Tuesday, 06.08.2024, 11:00
Statistical enrichment tools are highly useful in biological research. Current approaches to statistical enrichment in ranked or ordered lists such as, for example, GSEA and GOrilla, are limited to the suffix (prefix) of the list. These methods assess extreme density of 1s in binary vectors on either side. Statistical significance can be assigned using, e.g, Wilcoxon Rank Sum and mHG statistics.In this work we extend the mHG approach to also add...
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Learning In Joint Input And Downstream Task Optimization
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Tamir Shor
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Monday, 02.09.2024, 14:30
Traditional discriminative Machine-Learning approaches often formulate problems as optimization of a parameterized function mapping from a given input space to some desired output space. While this formulation is applicable to many theoretical and practical problems, it is inherently reliant on the assumption that the dataset X is constant. The world around us is abundant with scenarios where this is either not the case, or w...
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Interactions between Blockchain Networks Based on Market Analysis
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Ori Mazor
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Thursday, 11.07.2024, 16:30
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Zoom Lecture: 5701477766
Cryptocurrencies have gained popularity in recent years. They are often implemented on one or more of the over 1000 existing blockchain networks, including the popular Bitcoin and Ethereum networks. Recently, various technologies known as blockchain interoperability have been developed to connect these different blockchains, creating an interconnected blockchain ecosystem. Interoperability refers to the ability of blockchains to share information with each other. Decentralized Exc...
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Theory Seminar: Learning Probability Distributions; What Can, What Can't Be Done
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Shai Ben-David (University of Waterloo)
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Wednesday, 10.07.2024, 13:00
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Amado 814
Characterizing learnability by a combinatorial dimension is a hallmark of machine learning theory. Starting from the fundamental characterization of binary classification PAC by the VC-dimension, through the characterization of online mistake bound learnability by the Littlestone dimension, all the way to recent papers characterizing multi-class learning and differential privacy. However, for some basic learning setup no such characterizations have been provided. ...
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Large Scale Studies Of Deep Neural Networks For Uncertainty Estimation And Class-out-of-Distribution Detection
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Ido Galil
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Wednesday, 10.07.2024, 12:30
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Zoom Lecture: 92810808120 & Taub 9
In this seminar, I will discuss two of my papers (published in ICLR 2023) on uncertainty estimation and class-out-of-distribution detection. We present a novel framework to benchmark the ability of image classifiers to detect class-out-of-distribution (C-OOD) instances (i.e., instances whose true labels do not appear in the training distribution) at various levels of detection difficulty. We apply this technique to ImageNet, and benchmark 500+ pretrained, publicly available, Image...
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Spotlight Day - Nvidia
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Wednesday, 10.07.2024, 12:30
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CS Taub Lobby
First spotlight day of the semester!! Nvidia is coming to meet you in Taub Wednesday, July 10, between 12:30-2:30 PM in the Taub lobby In the program: a meeting with the recruitment team, the engineers waiting for you!!...
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Designing Language Models to Think Like Humans
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Chen Shani (Stanford)
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Wednesday, 10.07.2024, 12:30
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Taub 337
While language models (LMs) show impressive text manipulation capabilities, they also lack commonsense and reasoning abilities and are known to be brittle. In this talk, I will suggest a different LMs design paradigm, inspired by how humans understand it. I will present two papers, both shedding light on human-inspired NLP architectures aimed at delving deeper into the meaning beyond words. The first paper [1] accounts for the lack of commonsense and reasoning abilities by pr...
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Pixel Club - On The Benefits Of Models With Perceptually Aligned Gradients
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Roy Ganz - The Andrew and Erna Viterbi Faculty of Electrical & Computer Engineering
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Tuesday, 09.07.2024, 11:30
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Zoom Lecture: 94860001040
Deep learning has revolutionized computer vision, achieving unprecedented performanc in tasks like classification and detection. However, these models are highly susceptible to adversarial attacks, prompting the development of robust training methods. A notable outcome of such training is the phenomenon of Perceptually Aligned Gradients (PAG), where input gradients align semantically with human perception. Our research explores both the practical and theoretical implications of...
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Sequential Signal Mixing Aggregation For Message Passing Graph Neural Networks
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Almog David
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Wednesday, 03.07.2024, 11:00
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Room 014
Message Passing Graph Neural Networks (MPGNNs) have emerged as the standard method for modeling complex interactions across diverse graph entities. While the theory of such models is widely investigated, their aggregation module has not received sufficient attention. Sum-based aggregators have solid theoretical foundations regarding their separation capabilities. However, practitioners often prefer using more complex aggregations and mixtures of diverse aggregations. In this resea...
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Technipwn Group flies you to Vegas!
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Tuesday, 02.07.2024, 17:00
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Taub 9
Technipwn Group flies you to Vegas!This August, the faculty CTF group is participating in the DEFCON conference in Las Vegas and invites you to join!This coming tuesday we will hold a competition aimed at choosing the team that will fly to represent us at the conference.The topics of the competition are the usual topics of the ctf competitions such as: web, reverse, crypto, pwn and more!You are invited to prepare and come to compete ...
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Wrong Mathematical Proofs for Possibly Correct Claims: Implications and Applications in Cyber Security and Chip Design
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Prof. Oded Margalit (Ben Gurion University)
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Tuesday, 02.07.2024, 14:30
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Taub Auditorium 012
In this talk, we'll explore intriguing parallels between incorrect mathematical proofs and critical failures in technology, demonstrating their impact and lessons learned, like: 1. Mathematical Proofs and Social Engineering: How hand-waving a mathematical proof is similar to social engineering, and why larger hardware implementations might surprisingly be more efficient. 2. Cybersecurity and Mathematical Proofs: The surprising connection between a cyber attack that nearly caused a...
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What Can be Learned from Mixing Memory Pages of Different Sizes
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Mohammad Agbarya
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Monday, 01.07.2024, 14:00
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Zoom Lecture: 91705525071 & Taub 601
Cycle-accurate simulations, frequently used by computer architects, incur substantial overheads. To mitigate this, recent virtual memory studies have adopted a lighter-weight methodology that leverages partial simulations of only the memory subsystem. This approach feeds simulation outputs into a mathematical linear model to predict execution runtimes. While this methodology accelerates the simulation process, its accuracy has traditionally been assumed rather than rigorously v...
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Come be Part of the Faculty's CTF Group - Meeting on June 30th
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Sunday, 30.06.2024, 18:30
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Taub 9
Come be part of the Faculty's Capture The Flag - CTF group!! The faculty CTF group, Technipwn, holds bi-weekly meetings where we solve challenges, train for competitions and have fun The meetings are suitable for both beginners and experienced participants, and are held on Sundays at Taub 9. Organized and managed by students, and intended for all students (not only from computer science!), with and without CTF experience. The sessions include practical experience in solving chal...
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GradHC: Highly reliable Clustering Algorithm for DNA Storage Systems
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Dvir ben Shabat
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Sunday, 30.06.2024, 14:30
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Zoom Lecture: 5960823195
As data storage challenges grow and existing technologies approach their limits, synthetic DNA emerges as a promising storage solution due to its remarkable density and durability advantages. While cost remains a concern, emerging sequencing and synthetic technologies aim to mitigate it, yet introduce challenges such as errors in the storage and retrieval process. One crucial task in a DNA storage system is clustering numerous DNA reads into groups that represent the original i...
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ceClub: Advancing Computer Science with Digital Processing in Memory
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Orian Leitersdorf
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Sunday, 30.06.2024, 14:30
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Zoom Lecture: 93857585105 & Zisapel 608
The memory wall bottleneck is throttling the performance of data-intensive applications as the data transfer between the processing units (e.g., CPU, GPU cores) and the memory is significantly slower than the compute itself. Therefore, emerging digital processing-in-memory systems overcome this bottleneck by performing parallel bitwise logic within the memory arrays themselves. This enables a drastic reduction in data transfer for vectored operations since the same instruction may...
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ceClub: Enhancing Computer Performance with memristive Memory Processing Units: From General-Purpose Automation to DNA Sequencing Acceleration
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Rotem Ben Hur
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Sunday, 30.06.2024, 10:30
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Zoom Lecture: 92829605892 & Zisapel 608
Computer systems that facilitate tight integration of data storage and processing can eliminate the "memory wall" and "power wall" bottlenecks. The memristive Memory Processing Unit (mMPU) architecture contains memory cells that can also execute logical functions, such as Memristor-Aided Logic (MAGIC) NOR gates. The mMPU supports both general-purpose computing and application-specific acceleration. This research contributes to both these aspects of the mMPU.First, we intro...
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Advancing Molecular Frontiers: Redefining Optimization Goals in Drug Design
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Sally Turutov
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Thursday, 27.06.2024, 10:00
Deep learning has revolutionized drug development by enhancing various stages of the process, yet traditional optimization goals often lack the sophistication required for real-world applications. This work tackles more complex and nuanced problems beyond conventional property enhancement, focusing on optimizing under patentability constraints and translating preclinical success in animals to human clinical trials. In addressing patentability, we introduce a patent loss mechanism ...
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Theory Seminar: Fast Approximate Counting of Cycles
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Tomer Even (Technion)
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Wednesday, 26.06.2024, 13:00
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Amado 719
We consider the problem of approximate counting of triangles and longer fixed length cycles in undirected and directed graphs. We provide an algorithm which is faster as t, the number of copies of the searched subgraph, increases. Our running time, which significantly improves upon the state of the art (Tětek [ICALP’22]), is the same as that of multiplying an n x (n/t) matrix by an (n/t) x n matrix, up to polylogarithmic factors. Finally, we show that under popular fine-graine...
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CE Club: Persistent Memory Programming without Persistent Memory
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Gal Assa
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Wednesday, 26.06.2024, 11:30
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Zoom Lecture: 94673013539 & Zisapel 506
The arrival of persistent memory devices to consumer market has revived the interest in transactional durable algorithms. Persistent memory is touted as having two attributes that distinguish it from other storage technologies: fine access granularity and fast persistece.In the first part of the talk we investigate how these attributes differentiate persistent memory from block storage in the context of buffered durability – a relaxed approach that allows some progres...
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Pixel Club: Robust and Fast Volumetric Tomography of Natural Objects for Climate Studies
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Roi Ronen
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Tuesday, 25.06.2024, 11:30
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Zoom lecture & 1061, Meyer Building
Computed tomography (CT) aims to recover the volumetric three dimensional (3D) structure of heterogeneous objects. Traditionally, CT refers to a medical imaging modality. There the object, radiation source and detector array are fully controlled. This results in a linear image formation model. In contrast, we seek CT of natural objects, acquired outdoors, in an uncontrolled environment. We focus on underwater plankton and cloud droplets, which strongly affect climate. Cloud imagin...
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Multivariate Time Series Prediction
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Noam Koren
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Thursday, 20.06.2024, 16:30
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Zoom Lecture: 98850618360 & Taub 601
Multivariate time series forecasting is a pivotal task in several domains, including financial planning, medical diagnostics, and climate science. This paper presents the Neural Fourier Transform (NFT) algorithm, which combines multi-dimensional Fourier transforms with Temporal Convolutional Network layers to improve both the accuracy and interpretability of forecasts. The Neural Fourier Transform is empirically validated on fourteen diverse datasets, showing superior performance ...
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The Annual Faculty Hackathon is Underway! CS Hackathon - Doing Good
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Thursday, 20.06.2024, 08:00
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Taub Building
The annual Faculty Hackathon is underway! CS Hackathon - Doing Good Reserve the dates: June 20-21, in Taub. This year, in accordance with the order of the day, we will focus on developing technological solutions to increase mental resilience in cooperation with the Ministry of Defense's rehabilitation department, associations and initiatives. Opening of registration, development ideas, and preparation workshops - very soon. For details and more informat...
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Theory Seminar: Approximate Matrix Multiplication via Spherical Convolutions
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Omri Weinstein (Hebrew University)
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Wednesday, 19.06.2024, 13:00
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Amado 619
We develop a new framework, Polyform, for fast approximate matrix multiplication (AMM), through sums of sparse polynomial multiplications, using (variants of) FFT. Using this framework, we obtain new data-dependent speed-accuracy tradeoffs, which often improve on the worst-case accuracy of randomized sketching algorithms. Meanwhile, Polyform can be viewed as a cheap alternative bilinear operator to matrix multiplication in Deep Neural Networks, which is our motivating applicati...
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Quantitative Semantics on Jumping Finite Automata
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Ishai Salgado
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Sunday, 16.06.2024, 14:30
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Zoom Lecture: 94576770275 & Taub 301
Jumping automata are finite automata that read their input in a non-sequential manner, by allowing a reading head to “jump” between positions on the input, consuming a permutation of the input word. We argue that allowing the head to jump should incur some cost. To this end, we propose three quantitative semantics for jumping automata, whereby the jumps of the head in an accepting run define the cost of the run. The three semantics correspond to different interpretations of ju...
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Curvature Shift in Neural Networks
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Akiva Michael Block
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Sunday, 16.06.2024, 13:00
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Zoom Lecture: 94919856641 & Taub 9
Neural network optimization is a challenging task, in large part because of the nonconvexity, in general, of the loss function. Various algorithms have been proposed to solve this task, but most of them focus on the convex subspaces of the loss function to avoid the challenge of finding the optimal step in concave subspaces. In addition to avoiding the concave spaces entirely (which can bear a significant computational burden!), they also simply take the minimizer of a second-d...
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Protected Test-Time Domain Adaptation via Online Entropy Matching
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Yarin Bar
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Sunday, 16.06.2024, 11:00
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Taub 9
In this paper, we present a novel approach for test-time domain adaptation via online self-training, consisting of two components. First, we introduce a statistical framework that detects distribution shifts in the classifier's entropy values obtained on a stream of unlabeled samples. Second, we devise an online adaptation mechanism that utilizes the evidence of distribution shifts captured by the detection tool to dynamically update the classifier's parameters. The resulting adap...
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Pixel-Club:Volumetric Signal Recovery and Calibration in Atmospheric Lidar
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Adi Vainiger, The Andrew and Erna Viterbi Faculty of Electrical & Computer Engineering
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Monday, 10.06.2024, 15:00
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Room 1061, EE Meyer Building
Atmospheric lidars are important remote sensing tools in aerosols and climate research. A pulsed time-of-flight lidar continuously samples vertical atmospheric profiles, through day and night, yielding a spatiotemporal atmospheric map. However, lidar analysis is challenged by low signal-to-noise ratios, sunlight interference, and need for frequent calibration. We advance lidar analysis. We develop a framework for simulating realistic spatiotemporal lidar data under diverse atmosph...
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Covering All Bases: The Next Inning in DNA Sequencing Efficiency
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Hadas Abraham
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Sunday, 09.06.2024, 14:30
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Zoom Lecture:99533009512 & room 601
DNA emerges as a promising medium for the exponential growth of digital data due to its density and durability. This study extends recent research by addressing the coverage depth problem in practical scenarios, exploring optimal error-correcting code pairings with DNA storage systems to minimize coverage depth. Conducted within random access settings, the study provides theoretical analyses and experimental simulations to examine the expectation and probability distribution of sa...
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Theory Seminar: Explicit Codes for Poly-Size Circuits and Functions that are Hard to Sample on Low Entropy Distributions
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Ronen Shaltiel (Haifa University)
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Wednesday, 05.06.2024, 12:45
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Amado 719
In the talk I will survey a research direction which combines coding-theory and computational complexity. This direction was introduced by Lipton, and refined by Guruswami and Smith. The goal is to construct error correcting codes which correct errors that are introduced by computationally bounded channels. This is in contrast to Hamming’s standard model which assumes a bound on the fraction of bits that a channel may flip, but allows the channel to be computationally unbounded....
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CE-Club: Safe Deployment of Deep Learning Solutions for Rate Control Problems
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Noga Rotman, HUJI
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Wednesday, 05.06.2024, 11:30
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Zoom Lecture: 94673013539 & Meyer 861
In recent years, machine learning (ML) has fueled extraordinary advances in fields such as natural language processing and computer vision. These results have encouraged researchers to utilize ML in additional application domains, such as computer and networked systems, with varying degrees of success. In this talk I will focus on the prominent challenge of rate control in computer networking, and devising a practical ML toolkit for the safe deployment of deep-learning-based solut...
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The CTF Group Of The Faculty - Technipwn - Invites You To The Opening Lecture Of The Semester 4.6.2024
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Tuesday, 04.06.2024, 18:30
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Taub 1
The CTF group of the faculty - Technipwn invites you to the semester opening lecture - a year of offensive security: attacks on OpenAI, Atlassian, Apple and more! Speaker>> Ron Massas, Vulnerability Researcher at Imperva During his work at Imperva, security researcher Ron Massas uncovered a number of fascinating vulnerabilities and hacks in a number of large companies. In the lecture, he will take us on a fascinating journey in the world of offensive security, and will present c...
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Efficient, Correct and Durable Concurrent Algorithms
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Gal Sela
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Sunday, 02.06.2024, 13:30
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Zoom Lecture:97432970957
In the last two decades, a main way to improve performance of computer processors has been producing processors with multiple cores, on which tasks may execute concurrently. Software is required to keep up with the hardware advances and supply concurrent algorithms for programs that run on multiple cores. This talk will focus on a fundamental building block of concurrent algorithms: concurrent data structures, designed with improved efficiency while also satisfying strong correctn...
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Open day for undergraduate studies at the Technion May 31 in Sarona, Tel Aviv
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Friday, 31.05.2024, 10:00
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Sarona, Tel Aviv
An open day for undergraduate studies at the Technion will be held on May 31 from 10:00 am to 1:00 pm in Sarona, Tel Aviv. At the event you can meet the representatives of the faculty, consult, get an impression and get answers about the studies. Register for the open day at the ...
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Theory Seminar
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Theory group members and interested people
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Wednesday, 29.05.2024, 12:45
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Amado 619
This week we plan to get acclimated to our seminar's new location (outside of Taub, due to construction work), in a more social atmosphere. This includes introductions of current and prospective members of the group,* and talk about plans for the semester, including theory courses scheduled. Come meet established theorists and folks interested in theory research! * if you know students doing or interested in theory who are not (or might not be) registered to this mailing list, pl...
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Robustness Verification of Multi-Label Neural Network Classifiers
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Julian Mour
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Wednesday, 29.05.2024, 11:30
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Meyer 861 & Zoom Lecture: 91074303117
Multi-label neural networks are important in various tasks, including safety-critical tasks. Several works show that these networks are susceptible to adversarial attacks, which can remove a target label from the predicted label list or add a target label to this list. However, no verifier can deterministically determine the list of labels for which a multi-label neural network is locally robust. The main challenge is that the complexity of the analysis increases by a factor expon...
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CE-Club: Robustness Verification of Multi-Label Neural Network Classifiers
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Julian Moure
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Wednesday, 29.05.2024, 11:30
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Zoom Lecture: 91074303117 & Meyer 861
Multi-label neural networks are important in various tasks, including safety-critical tasks. Several works show that these networks are susceptible to adversarial attacks, which can remove a target label from the predicted label list or add a target label to this list. However, no verifier can deterministically determine the list of labels for which a multi-label neural network is locally robust. The main challenge is that the complexity of the analysis increases by a factor expon...
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The Sky Is The Limit - An Open Day For Advanced Degree Studies At The Faculty
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Wednesday, 22.05.2024, 13:00
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Taub 337
A meeting of those interested in graduate studies at the Taub Faculty of Computer Science at the Technion will be held on Wednesday, May 22, 2024, 1:00 p.m., room 337 Outstanding bachelor's graduates from all universities! This is your opportunity to participate and be impressed by the Faculty of Computer Science at the Technion, Meet faculty members and graduate students and hear fascinating lectures. Event schedule: 13:00-13:30 Opening remarks: The words of t...
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CE-Club: Survivable Payment Channel Networks
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Yekaterina Podiatchev
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Wednesday, 22.05.2024, 11:30
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Meyer 861
Payment Channel Networks (PCNs) are a leading method to scale the transaction throughput in cryptocurrencies. Two participants can use a bidirectional payment channel for making multiple mutual payments without committing them to the blockchain. Opening a payment channel is a slow operation that involves an on-chain transaction locking a certain amount of funds. These aspects limit the number of channels that can be opened or maintained. Users may route payments through a multi-ho...
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Structural Language Models for Code
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Shaked Brody
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Thursday, 16.05.2024, 14:00
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Zoom Lecture:92691399579
In the past few years, software has been at the heart of many applications ranging from appliances to virtual services. Helping software developers to write better code is a crucial task. In parallel, recent developments in machine learning and deep learning in particular have shown great promise in many fields, and code-related tasks in particular. The main challenge is how to represent code in a way that can be used by deep learning models effectively. While code can be treated ...
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Jumping Automata over Infinite Words
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Omer Yizhaq
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Wednesday, 15.05.2024, 15:30
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Zoom lecture: 95929737670, password: OmerMSC and room 601
We introduce and study jumping automata over infinite words, a fascinating twist on traditional finite automata. These machines read their input in a non-consecutive manner, defying conventional word order. We explore three distinct semantics: one ensuring every letter is accounted for, another permitting word permutation within fixed windows, and a third allowing permutation within windows of an existentially-quantified bound. Our work covers expressiveness, closure properties, a...
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CIQA : A Coding Inspired Question Answering Model
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Mousa Arraf
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Sunday, 05.05.2024, 15:00
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Zoom Lecture:91070061962
Methods in question-answering (QA) that transform texts detailing processes into an intermediate code representation, subsequently executed to generate a response to the presented question, have demonstrated promising results in analyzing scientific texts that describe intricate processes. The limitations of these existing text-to-code models are evident when attempting to solve QA problems that require knowledge beyond what is presented in the input text. We propose a novel domai...
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Blockchain Loans: Mechanisms, Platforms And Challenges
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Tom Azoulay
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Sunday, 21.04.2024, 16:00
Distributed lending protocols are major financial mechanisms that match borrowers and lenders without the need for intermediaries. Smart contracts deployed on blockchains ensure the security of such loans. Borrowers mitigate the risk of default by providing collateral in the form of cryptocurrencies or by limiting the loan duration. In the first part of the talk, we describe various loan types, major platforms, and financial models that allow them. In the second part of the talk,...
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Pixel Club: Deep Computational Imaging: Optimal sensing, reconstruction, and uncertainty quantification
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Elias Nehme - The Andrew and Erna Viterbi Faculty of Electrical & Computer Engineering
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Tuesday, 16.04.2024, 14:30
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Room 1061, EE Meyer Building & Zoom Lecture:5049603009
In biological imaging, fast acquisition of depth information is crucial e.g. for accurate 3D tracking of sub-cellular elements and for 3D super-resolution. In the first part of this talk, we present a series of works enhancing the success of snapshot depth sensing in the revolutionary field of single-molecule localization microscopy (Nobel Prize in Chemistry 2014). Specifically, we present an approach for jointly designing the “optics” of the microscope and the 3D reconstructi...
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Deep Learning and Tree Search-Based Policy Optimization under Stochastic Execution Delay
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David Valensi
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Monday, 15.04.2024, 14:00
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Zisapel 413 & Zoom Lecture: 98471388934
The standard formulation of Markov decision processes (MDPs) assumes that the agent's decisions are executed immediately. However, in numerous realistic applications such as robotics or healthcare, actions are performed with a delay whose value can even be stochastic. In this work, we introduce stochastic delayed execution MDPs, a new formalism addressing random delays without resorting to state augmentation. We show that given observed delay values, it is sufficient to perform a ...
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A VIP Visit At The Technion For Children Of Graduates
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Monday, 15.04.2024, 10:00
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Technion, Ulman Building
Graduates of the faculty are invited with their children to a day of lectures, workshops and information regarding registration and admission - for children; and a nostalgic tour (for parents) Monday, April 15, starting at 10:00 at the Technion In the program: 1. The wonders of infinity - the Faculty of Mathematics 2. What is the Internet of Things? - Faculty of Computer Science 3. Games and Virtual Reality - Fac...
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CE-Club: Buffer Isolation With Imperfect Congestion Control Classification
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Yara Mulla ( NVidia - IBC Barracuda)
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Wednesday, 10.04.2024, 11:30
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Zoom Lecture: 83464479226
Due to their increasing aggressiveness, recent congestion control algorithms (CCAs) can quickly starve standard TCP flows in their shared router queues. Existing solutions based on fair queueing are not scalable enough, and those based on admission control do not fit all CCAs. Independently, building on the popularization of machine learning, recent papers have designed several CCA classifiers.In this seminar, we introduce a buffer isolation mode where incoming flows first...
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Pixel Club: FreeAugment: Data Augmentation Search Across All Degrees of Freedom
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Tom Bekor - The Andrew and Erna Viterbi Faculty of Electrical & Computer Engineering
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Tuesday, 09.04.2024, 11:30
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Room 1061, EE Meyer Building
Graduate Seminar Data augmentation has become an integral part of deep learning, as it is known to improve the generalization capabilities of neural networks.Since the most effective set of image transformations differs between tasks and domains, automatic data augmentation search aims to alleviate the extreme burden of manually finding the optimal image transformations. However, current methods are not able to jointly optimize all degrees of freedom: (1)...
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PAT-CEP : Statistical Guarantee for ML-based Complex Event Processing
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Nadav Rubinstein
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Tuesday, 09.04.2024, 11:00
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Zoom Lecture:94644097135
In the landscape of data stream processing, the challenges posed by online problems are of paramount importance. This paper introduces a pioneering method tailored to address these challenges within the context of data streams. While our initial focus centered on Complex Event Processing (CEP) problems, it is essential to underscore the versatility of our approach, as it is equally applicable to a diverse range of online problems. To the best of our knowledge, there exists no comp...
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TDC Seminar: Fault-Tolerant Labeling and Compact Routing Schemes
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Michal Dory, Haifa University
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Monday, 08.04.2024, 13:30
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Zisapel (ECE) 608
Assume that you have a huge graph, where edges and vertices may fail, and you want to answer questions about this graph quickly, without inspecting the whole graph. A fault-tolerant labeling scheme allows us to do just that. It is a distributed data structure, in which each vertex and edge is assigned a short label, such that given the labels of a pair of vertices s,t, and a set of failures F, you can answer questions about s and t in G\F. For example, determine if s and t are con...
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DEPTH: Discourse Education through Pre-Training Heirarchically
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Zachary Elisha Bamberger
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Sunday, 07.04.2024, 10:00
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Room 601
Language Models (LMs) excel in many tasks, but understanding discourse – how sentences connect to form coherent text – remains a challenge. This is especially true for smaller models aiming to match the abilities of their larger counterparts in handling long and complex inputs. To address this, we introduce DEPTH, a new encoder-decoder model designed to foster robust discourse-level representations during the pre-training phase. DEPTH uniquely combines hierarchical sentence re...
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Learning with visual foundation models for Gen AI
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Gal Chechik, Bar-Ilan University and NVIDIA
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Thursday, 04.04.2024, 10:30
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Taub 337
Between training and inference, lies a growing class of AI problems that involve fast optimization of a pre-trained model for a specific inference task. These are not pure “feed-forward” inference problems applied to a pre-trained model, because they involve some non-trivial inference-time optimization beyond what the model was trained for; neither are they training problems, because they focus on a specific input. These compute-heavy inference workflows raise new challenges i...
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CS RESEARCH DAY 2024
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Wednesday, 03.04.2024, 12:30
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CS Taub Lobby
The 12th CS Research Day for graduate studies will be held on Wednesday, April 03, 2024 between 12:30-14:30, at the lobby of the CS Taub Building. Research Day events are opportunity for our graduate students to expose their researches using posters and presentations to CS faculty and all degrees students, Technion distinguished representatives and to high-ranking delegates from the hi-tech leading industry companies in Israel and abroad. The participating researches will be on...
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Theory Seminar: Toward Better Depth Lower Bounds: A KRW-like theorem for Strong Composition
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Or Meir (Haifa University)
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Wednesday, 03.04.2024, 12:15
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Taub 201
One of the major open problems in complexity theory is proving super-logarithmic lower bounds on the depth of circuits. Karchmer, Raz, and Wigderson (Computational Complexity 5(3/4), 1995) suggested approaching this problem by proving that depth complexity of a composition of two functions is roughly the sum of their individual depth complexities. They showed that the validity of this conjecture would imply the desired lower bounds.The intuition that underlies the KRW conj...
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CE-Club:Here Comes the GenAI Malware, Worm, and APT
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Ben Nassi, Technion
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Wednesday, 03.04.2024, 11:30
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Meyer 861
In the past year, numerous companies have incorporated Generative AI (GenAI) capabilities into new and existing applications, forming interconnected Generative AI (GenAI) ecosystems consisting of applications powered by GenAI services.While ongoing research highlighted risks associated with the GenAI layer of agents (e.g., dialog poisoning, membership inference, prompt leaking, jailbreaking), a critical question emerges: Can attackers develop malware to exploit the GenAI c...
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Marrying Vision and Language: A Mutually Beneficial Relationship?
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Hadar Averbuch-Elor, Tel-Aviv University
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Tuesday, 02.04.2024, 14:30
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Taub 337
Foundation models that connect vision and language have recently shown great promise for a wide array of tasks such as text-to-image generation. Significant attention has been devoted towards utilizing the visual representations learned from these powerful vision and language models. In this talk, I will present an ongoing line of research that focuses on the other direction, aiming at understanding what knowledge language models acquire through exposure to images during pretraini...
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Pixel-Club: STMPL: Human Soft-Tissue Simulation
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Anton Agafonov (Graduate Seminar)
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Tuesday, 02.04.2024, 11:30
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Room 608, Zisapel Building
In various applications, such as virtual reality and gaming, simulating the deformation of soft tissues in the human body during interactions with external objects is essential. Traditionally, Finite Element Methods (FEM) have been employed for this purpose, but they tend to be slow and resource-intensive. In this paper, we propose a unified representation of human body shape and soft tissue with a data-driven simulator of non-rigid deformations. This approach enables rapid simula...
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StarkWare - Engineering the Future of Blockchain
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StarkWare
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Monday, 01.04.2024, 12:30
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The graduate students' lounge, room 225
Engineering the Future of Blockchain 1.4.23 | 12:30-14:30 | The graduate students' lounge, Taub, 2nd floor 12:30 - Mingling and Snacks 13:00 - Oded Naor, Ph.D., Product Manager - Btockchain reinvented: a deep dive into StarkWare's game-changing sotutions 13:30 - Noa Oved, MSC, Software Team Lead - Coding the future: Transforming algorithmic insights into real-wortd sotutions 14:00- Q&A Plese RSVP at...
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Open day for March 28. Getting Started!
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Thursday, 28.03.2024, 09:30
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Technion
An open day for studies at the Technion will be held on Thursday, March 28, starting at 09:30 For details and registration, go to the registration and admission website at the link ...
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Theory Seminar: Exploring the Generalization Ability of (Convex) Optimization Algorithms
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Tomer Koren (Tel-Aviv University)
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Wednesday, 27.03.2024, 12:15
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Taub 201
In machine learning, there has been considerable interest over the past decade in understanding the ability of optimization algorithms to generalize—namely, to produce solutions (models) that extend well to unseen data—particularly in the context of overparameterized problems. I will survey several recent theoretical studies that explore generalization in classical convex optimization, that reveal intriguing behavior of common optimization methods and shed some light on the c...
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Guest seminar - How to design innovative software?
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Prof. Daniel Jackson, MIT
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Wednesday, 27.03.2024, 12:00
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Auditorium 012, floor 0
I will explain how successful innovations in software can usually be traced to just one or two "concepts" that offer new scenarios that, with seemingly small shifts, radically change how an application is used. I give examples from apps such as Zoom, WhatsApp and Calendly. I explain how concepts, each with their own characteristic scenarios, can be composed to form apps. I explain how this idea can be used to make software more usable, modular and consistent. More information at:...
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CE-Club: Optimizing Information Freshness in Wireless Networks: From Theory to Implementation
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Eytan Modiano - Laboratory for Information and Decision Systems Massachusetts Institute of Technology
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Wednesday, 27.03.2024, 11:30
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Meyer 861
Age of Information (AoI) is a recently proposed performance metric that captures the freshness of the information from the perspective of the application. AoI measures the time that elapsed from the moment that the most recently received packet was generated to the present time. In this talk, we explore the AoI optimization problem in wireless networks.We start by considering a wireless network with a number of nodes transmitting information to a base station and develop l...
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Intel's tech experience is coming to campus!
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Wednesday, 27.03.2024, 10:00
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EE Meyer Building
Intel's tech experience is coming to campus! Ready for the most innovative technological picnic you've ever seen? We have loaded technological tools and our greatest minds to the track and we are on our way to you Wednesday 27.3 | Mayer building, 3rd floor 10:00 - AR | VR | HR Come and get to know us and our technologies 12:30 - FPGA MicroPython The number of places is limited, register at the ...
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Pixel-Club: Idempotent Generative Network
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Assaf Shocher, NVIDIA
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Tuesday, 26.03.2024, 11:30
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Room 1061, EE Meyer Building
We propose a new approach for generative modeling based on training a neural network to be idempotent. An idempotent operator is one that can be applied sequentially without changing the result beyond the initial application, namely f(f(z))=f(z). The proposed model f is trained to map a source distribution (e.g, Gaussian noise) to a target distribution (e.g. realistic images) using the following objectives: (1) Instances from the target distribution should map to themselves, namel...
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The Altru-Egoistic Approach to Collaborative Caching
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Amir Dachbash
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Thursday, 21.03.2024, 10:30
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Zoom Lecture:93387090038
In this lecture we will explore collaborative caching algorithms in order to boost the effectiveness of caches in a distributed storage system. I'll introduce a scheme that partitions each node’s cache into two conceptual regions: an egoistic area whose goal is to contain the most valuable data for the node that owns the cache, and an altruistic area whose goal is to contain the most valuable data for the system as a whole. Each node’s division between these two regions is dyn...
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Pixel-Club: Explaining Classification by Image Decomposition
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Elnatan Kadar (Graduate Seminar)
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Wednesday, 20.03.2024, 14:30
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Room 1061, EE Meyer Building
We propose a new way to explain and to visualize neural network classification through a decomposition-based explainable AI. Instead of providing an explanation heatmap, our method yields a decomposition of the image into class-agnostic and class-distinct parts, with respect to the data and chosen classifier. Following a fundamental signal processing paradigm of analysis and synthesis, the original image is the sum of the decomposed parts. We thus obtain a radically different way ...
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Theory Seminar: Deterministic Online embedding of metrics
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Ilan Newman (University of Haifa)
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Wednesday, 20.03.2024, 13:15
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Taub 201
A finite metric space $(X,d)$ on a set of points $X$ is just the shortest path metric $d$ on a positively weighted graph $G=(X,E)$. In the online setting, the vertices of the input finite metric space $(X,d)$ are exposed one by one, together with their distances $d(*,*)$to the previously exposed vertices. The goal is to embed (map) $X$ into a given host metric space $(H,d_H)$ (finite or not) and so to distort the distances as little as possible (distortion is the worst cas...
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Mobileye Spotlight Day
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Wednesday, 20.03.2024, 12:30
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Taub Building
You are invited to the spotlight day of the Mobileye company at the Technion Wednesday 20.3 | 12:30 | Taub Building...
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ceClub: From Dashboards To Labels: Helping Users Manage And Make Decision About Privacy
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(George Washington University) Adam J Aviv
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Wednesday, 20.03.2024, 11:30
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Meyer 861 & Zoom Lecture:94673013539
The surveillance economy, where tracking and collecting data on uses for the purpose of advertising and other actions, is central to much of the money-making enterprises of the modern technology ecosystem. Due to regulations and other forces, some of the largest companies, such as Google and Apple, have prioritized mechanisms for users to better manage and receive information about the kinds of data that is being collected about them. In this talk, I will explore how effective the...
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Yahoo Is Coming To The Faculty On March 19 - Summer Internships And Research Opportunities
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Tuesday, 19.03.2024, 12:30
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CS Grads Club, Room 225
Yahoo holds a dedicated meeting with graduate students Tuesday, March 19 at 12:30 p.m. at the CS Grads Club In the program: an introduction to Yahoo's research in Israel and the summer internship program. Register to the event here waiting for you!!...
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Nvidia - Lecture And Pizza
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Yarden Zuckerman, SW Security Manager, Nvidia
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Monday, 18.03.2024, 18:00
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Auditorium 012, floor 0
Join us for a lecture and pizza! Cyber Security Challenges In The Modern Era by Yarden Zuckerman, SW Security Manager, Nvidia Monday | March 18, 2024 | 18:00 p.m. | Piano Auditorium Taub Building ...
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TDC Seminar: Null Messages, Information and Coordination
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Raissa Nataf
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Monday, 18.03.2024, 13:30
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Zisapel (ECE) 608
I'll present our paper about the role that null messages play in synchronous systems with and without failures. Our work provides necessary and sufficient conditions on the structure of protocols for information transfer and coordination there. We start by introducing a new and more refined definition of null messages. A generalization of message chains that allow these null messages is provided and is shown to be necessary and sufficient for information transfer in reliable syste...
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Theory Seminar: A Unified Characterization Of Private Learning
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Hilla Schefler (Technion)
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Wednesday, 13.03.2024, 12:15
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Taub 201
Differential Privacy (DP) is a mathematical framewirk for ensuring the privacy of individuals in a dataset. Roughly speaking, it guarantees that privacy is protected in data analysis by ensuring that the output of an analysis does not reveal sensitive information about any specific individual, regardless of whether their data is included in the dataset or not.This talk presents a unified framework for characterizing both pure and approximate differentially private learnabi...
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Window-Based Distribution Shift Detection for Deep Neural Networks‏
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Guy Bar-Shalom
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Wednesday, 13.03.2024, 10:30
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Zoom Lecture:97086749422 & Meyer 1061
To deploy and operate deep neural models in production, the quality of their predictions, which might be contaminated benignly or manipulated maliciously by input distributional deviations, must be monitored and assessed. Specifically, we study the case of monitoring the healthy operation of a deep neural network (DNN) receiving a stream of data, with the aim of detecting input distributional deviations over which the quality of the network’s predictions is potentially damaged. ...
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Active Propulsion Noise Shaping For Multi-Rotor Aircraft Localization
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Gabriele Serussi
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Tuesday, 12.03.2024, 14:30
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Zoom Lecture:99864029841 and Taub 401
Multi-rotor aerial autonomous vehicles (MAVs) primarily rely on vision for navigation purposes. However, visual localization and odometry techniques suffer from poor performance in low or direct sunlight, a limited field of view, and vulnerability to occlusions. Acoustic sensing can serve as a complementary or even alternative modality for vision in many situations, and it also has the added benefits of lower system cost and energy footprint, which is especially important for micr...
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Pixel-Club: Using Zodiacal Light For Spaceborne Calibration Of Polarimetric Imagers
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Or Avitan (Graduate Seminar)
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Tuesday, 12.03.2024, 11:30
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Room 1061, EE Meyer Building
We propose that spaceborne polarimetric imagers can be calibrated, or self-calibrated using zodiacal light (ZL). ZL is created by a cloud of interplanetary dust particles. It has a significant degree of polarization in a wide field of view. From space, ZL is unaffected by terrestrial disturbances. ZL is insensitive to the camera location, so it is suited for simultaneous cross-calibration of satellite constellations. ZL changes on a scale of months, thus being a quasi-constant tar...
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TDC Seminar: From Distributed Computing to Cryptography and Back
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Ittai Abraham, Intel
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Monday, 11.03.2024, 13:30
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Zisapel (ECE) 608
I will share some of my learnings from working on problems on the intersection of Distributed Computing and Cryptography.On the one hand, I will show how some cryptographic protocols (MPC and DKG) can be improved by using distributed computing counterparts for notions such as zero knowledge proofs and proofs of knowledge. On the other hand, I will show how distributed computing protocols (ABA) can be improved by carefully using notions of binding from cryptography. One rec...
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On the Robustness of Dialogue History Representation in Conversational Question Answering: A Comprehensive Study and a New Prompt-based Method
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Zorik Gekhman
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Monday, 11.03.2024, 10:30
Most works on modeling the conversation history in Conversational Question Answering (CQA) report a single main result on a common CQA benchmark. While existing models show impressive results on CQA leaderboards, it remains unclear whether they are robust to shifts in setting (sometimes to more realistic ones), training data size (e.g. from large to small sets) and domain. In this work, we design and conduct the first large-scale robustness study of history modeling approaches for...
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Nvidia Invites You To a Virtual Spotlight Day 10/3
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Sunday, 10.03.2024, 18:00
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Meet virtually
Nvidia invites you to a virtual spotlight day where the company's engineers will talk about the different groups and open positions Sunday, March 10, from 18:00 to 19:30 To register for the event here...
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Cadence Arrive For Recruitment Day At The Faculty
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Wednesday, 06.03.2024, 12:30
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CS Taub Lobby
Cadence company is coming to a spotlight day at the faculty Wednesday 6/3 | 12:30-14:30 | Lobby Taub In the program: a meeting with the recruitment teams, the engineers for a 1:1 conversation about employment opportunities and tips for writing a report. And of course merch and sweets. waiting for you!!...
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Faster Matrix Game Solvers Via Ball Oracle Acceleration
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Yair Carmon (Tel-Aviv university)
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Wednesday, 06.03.2024, 12:15
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Taub 201
We design a new stochastic first-order algorithm for approximately solving matrix games as well as the more general problem of minimizing the maximum of smooth convex functions. Our central tool is ball oracle acceleration: a technique for minimizing any convex function with a small number of calls to a ball oracle that minimizes the same function restricted to a small ball around the query point. To design an efficient ball oracle for our problems of interest we leverage stochast...
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Early Time Classification with Accumulated Accuracy Gap Control
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Liran Ringel
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Tuesday, 05.03.2024, 15:00
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Zoom Lecture:96835343656 and Taub 401
Early time classification algorithms aim to label a stream of features without processing the full input stream, while maintaining accuracy comparable to that achieved by applying the classifier to the entire input. In this paper, we introduce a statistical framework that can be applied to any sequential classifier, formulating a calibrated stopping rule. This data-driven rule attains finite-sample, distribution-free control of the accuracy gap between full and early-time classifi...
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Mor Filo, a graduate of the faculty and a developer at Amazon
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Monday, 04.03.2024, 18:30
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Auditorium 012, floor 0
You have been accepted as a student! What now? The student community at the SHE S faculty invites you to a meeting on: First time student job: about the opportunities, challenges and skills you acquire in your first job Monday, 4/3 at 6:30 pm in the piano auditorium Please register in advance: here Speaker: Moore Philo, graduate of the faculty and developer at Amazon The meeting is suitable for thos...
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Stable Tuple Embeddings for Dynamic Databases
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Neta Friedman
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Thursday, 29.02.2024, 15:00
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Zoom Lecture: 99751665591
We study the problem of computing an embedding of the tuples of a relational database in a manner that is extensible to dynamic changes of the database. In this problem, the embedding should be stable in the sense that it should not change on the existing tuples due to the embedding of newly inserted tuples (as database applications might already rely on existing embeddings); at the same time, the embedding of all tuples, old and new, should retain high quality. This task is chall...
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Spotlight Day For Nvidia At The Technion
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Wednesday, 28.02.2024, 12:30
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CS Taub Lobby
Spotlight day for Nvidia at the Technion on February 28, 2024 Nvidia is coming to meet the students of the Faculty of Computer Science at the Technion! Come and meet the company's engineers face to face Wednesday February 28, 2024 | 12:30-14:30 | Taub lobby, floor 0...
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Distance Sensitivity Oracles
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Sarel Cohen (Tel-Aviv Academic College)
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Wednesday, 28.02.2024, 12:15
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Taub 201
Theory Seminar: An f-edge fault-tolerant distance sensitivity oracle (f-DSO) is a data-structure that, when queried with two vertices (s, t) and a set F of at most f edges of a graph G with n vertices, returns an estimate tilde{d}(s,t,F) of the distance d(s,t,F) from s to t in G – F. The oracle has stretch alpha if the estimate satisfies d(s,t,F) le tilde{d}(s,t,F) le alpha cdot d(s,t,F) . In the last two decades, extensive research has focused on developing efficient f-DSOs. Th...
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TDC Seminar: Fast and Fair Lock-Free Locks
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Naama Ben-David, Technion
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Monday, 26.02.2024, 13:30
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Zisapel (ECE) 608
Locks are frequently used in concurrent systems to simplify code and ensure safe access to contended parts of memory. However, they are also known to cause bottlenecks in concurrent code, leading practitioners and theoreticians to sometimes opt for more intricate lock-free implementations. In this talk, I’ll show that, despite the seeming contradiction, it is possible to design practically and theoretically efficient lock-free locks; I'll present a lock-free lock algorithm with ...
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Fundamental Problems in AI: Transferability, Compressibility and Generalization
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Tomer Galanti
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Thursday, 22.02.2024, 15:00
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Zoom Lecture:9316005503 Passcode: 272625
In this talk, we delve into several fundamental questions in deep learning. We start by addressing the question, "What are good representations of data?" Recent studies have shown that the representations learned by a single classifier over multiple classes can be easily adapted to new classes with very few samples. We offer a compelling explanation for this behavior by drawing a relationship between transferability and an emergent property known as neural collapse. Later, we expl...
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Theory and Practice of DNA Storage
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Daniella Bar-Lev
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Wednesday, 21.02.2024, 17:00
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Zoom Lecture: 92916633492 and Taub 9
In the last decade, DNA-based storage systems emerged as a potential data archival solution due to their high data density and durability. This research delves into intrinsic error characteristics of DNA storage systems to devise robust coding strategies and innovative algorithms for enhanced reliability, efficiency, scalability, and cost-effectiveness. The research propels DNA storage feasibility while contributing to foundational theory.The work analyzes combinatorial st...
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Identifying Underlying Geometry To Analyze High-Dimensional Data: Images And Shape Spaces As A Case Study
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Shira Faigenbaum-Golovin
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Wednesday, 21.02.2024, 15:00
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Zoom Lecture:93613579310 Passcode: 652820
High-dimensional data is increasingly available in diverse applications, ranging from images to shapes represented as point clouds. Such data raises novel questions and offers a unique opportunity to study them by developing new machine-learning tools. While the analysis of an individual sample may be challenging, leveraging the power of the data collection can be effective in tackling complex tasks. This talk delves into the challenges associated with studying such data, particul...
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Theory Seminar: IOPs with Inverse Polynomial Soundness Error
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Gal Arnon (Weizmann institute)
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Wednesday, 21.02.2024, 12:15
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Taub 201
We show that every language in NP has an Interactive Oracle Proof (IOP) with inverse polynomial soundness error and small query complexity. This achieves parameters that surpass all previously known PCPs and IOPs. Specifically, we construct an IOP with perfect completeness, soundness error 1/n, round complexity O(loglog n), proof length poly(n) over an alphabet of size O(n), and query complexity O(loglog n). This is a step forward in the quest to establish the sliding-scale conjec...
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TDC Seminar: Deterministic Distributed Maximum Weight Independent Set Approximation in Sparse Graphs
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Yuval Gil, Technion
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Monday, 19.02.2024, 13:30
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Zisapel (ECE) 608
This talk focuses on the distributed task of constructing an approximate \emph{maximum weight independent set (MWIS)}. Specifically, we are interested in deterministic CONGEST algorithms whose approximation guarantees are expressed as a function of the graph's \emph{arboricity} $\alpha$.Generally speaking, efficient deterministic non-trivial approximation algorithms for MWIS were not known until the recent breakthrough of Faour et al.~[SODA 2023] that obtained an $O(\Delta...
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A Deep Learning Platform for Diagnosing ECG Tests
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Idan Levy
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Thursday, 15.02.2024, 11:00
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Zoom Lecture: Link and Taub 401
In clinical settings, a significant portion of ECG data is typically available in printed form, and the most convenient means of digitizing this information involves utilizing a mobile device. Despite notable progress in AI-based techniques for paper-based 12-lead ECG analysis, their adoption in clinical practice remains limited primarily due to challenges such as inadequate accuracy in clinical settings and a restricted ability to diagnose various cardiac conditions. Our objectiv...
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Theory Seminar: Optimal Prediction Using Expert Advice and Randomized Littlestone Dimension
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Idan Mehalel (Technion)
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Wednesday, 14.02.2024, 12:15
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Taub 201
Suppose that n forecasting experts (or functions) are providing daily rain/no-rain predictions, and the best among them is mistaken in at most k many days. For how many days will a person allowed to observe the predictions, but has no weather-forecasting prior knowledge, mispredict?In this talk, we will discuss how such classical problems can be reduced to calculating the (average) depth of binary trees, by using newly introduced complexity measures (aka dimensions) of the...
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ceClub: Space-efficient FTL for Mobile Storage via Tiny Neural Nets
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Ron Marcus
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Wednesday, 14.02.2024, 11:30
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Meyer 861
With the rapid increase of storage demands and working sets of modern mobile apps, maintaining high I/O performance in mobile SSDs under strict resource constraints is challenging. The Flash Translation Layer (FTL) must increase the capacity of the Logical-To-Physical (L2P) address translation cache to keep up with the new workloads, but it comes at the cost of scaling the on-die SRAM, resulting in higher chip area, power consumption, and costs.In this talk, I will present...
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Technion CTF Team
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Tuesday, 13.02.2024, 18:30
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Taub 2
Come be part of a new Capture The Flag-CTF group at the Faculty The meetings are held every Tuesday at 18:30 at Taub 9 and include guest lectures and practical experience in solving challenges. Everybody is invited! Beginners and experienced For details: Technionctf.com This week - February 13, 2024: 18:30 | Taub 2 | Omar Atias - security researcher, lecturer at BlackHat USA & DEFCON The price of con...
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A 0-RTT-Aware QUIC Load Balancer
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Robert Shahla
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Monday, 12.02.2024, 12:00
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Zoom Lecture: 97318309550 and Taub 601
QUIC is an emerging transport protocol, offering multiple advantages over TCP. Yet, to fully unleash QUIC’s potential, a paradigm shift is needed in existing network infrastructure. We propose a novel 0-RTT-aware load balancing algorithm. 0-RTT is crucial for web performance, particularly on mobile networks. Our load balancing algorithm ensures 0-RTT while maintaining near-optimal load balancing performance.Through extensive simulations, using both synthetic and real-wor...
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Final Spotlight Day
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Wednesday, 07.02.2024, 12:30
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Auditorium 012, floor 0
You are invited to Final spotlight day Wednesday 07.02.2024 | 12:30-14:30 | Visitor Center Auditorium 012, Floor 0 12:30 - Come meet engineers, researchers and the recruitment team at Final, and get to know the day-to-day life at Final. 13:15 - Meeting on options, probabilities and the world of algorithm trading | Noam Horowitz - researcher at Final To register for the lecture click ...
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Theory Seminar: Algorithmic Cheap Talk
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Konstantin Zabaranyi (Technion)
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Wednesday, 07.02.2024, 12:15
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Taub 201
Come be part of a new Capture The Flag-CTF group at the Faculty The meetings are held every Tuesday at 18:30 at Taub 9 and include guest lectures and practical experience in solving challenges. Everybody is invited! Beginners and experienced For details: Technionctf.com The week of February 6, 2024: Beginners: Forensics & Networks | Taub 9 experienced: Challenges from 2023 LA CTF | Tau...
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Technion CTF Team
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Tuesday, 06.02.2024, 18:30
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Taub 9
Come be part of a new Capture The Flag-CTF group at the Faculty The meetings are held every Tuesday at 18:30 at Taub 9 and include guest lectures and practical experience in solving challenges. Everybody is invited! Beginners and experienced For details: Technionctf.com The week of February 6, 2024: Beginners: Forensics & Networks | Taub 9 experienced: Challenges from 2023 LA CTF | Taub 8...
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Constrictor: Immutability as a Design Concept
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Elad Kinsbruner
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Tuesday, 06.02.2024, 12:30
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Taub 601
Many object-oriented applications in algorithm design rely on objects never changing during their lifetime. This is often tackled by marking object references as read-only, e.g., using the const keyword in C++. In other languages like Python or Java where such a concept does not exist, programmers rely on best practices that are entirely unenforced. While reliance on best practices is obviously too permissive, const-checking is too restrictive: it is possible for a method to mutat...
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Pixel-Club: Robustified ANNs Reveal Wormholes Between Human Category Percepts
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Guy Gaziv (DiCarlo Lab at MIT)
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Tuesday, 06.02.2024, 11:30
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Room 1061, EE Meyer Building
The visual object category reports of artificial neural networks (ANNs) are notoriously sensitive to tiny, adversarial image perturbations. Because human category reports (aka human percepts) are thought to be insensitive to those same small-norm perturbations — and locally stable in general — this argues that ANNs are incomplete scientific models of human visual perception. Consistent with this, we show that when small-norm image perturbations are generated by standard ANN mo...
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Theory Of Crypto Seminar: Perfect Asynchronous MPC with Linear Communication Overhead
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Gilad Asharov (Bar Ilan University)
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Thursday, 01.02.2024, 11:30
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Taub 401
We study secure multiparty computation in the asynchronous setting with perfect security and optimal resilience (less than one-fourth of the participants are malicious). It has been shown that every function can be computed in this model [Ben-OR, Canetti, and Goldreich, STOC'1993]. Despite 30 years of research, all protocols in the asynchronous setting require $\Omega(n^2C)$ communication complexity for computing a circuit with $C$ multiplication gates. In contrast, for nearly 15...
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Almost Logarithmic Approximation for Cutwidth and Pathwidth
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Dor Katzelnick
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Wednesday, 31.01.2024, 12:30
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Taub 201
We study several graph layout problems with a min max objective. Here, given a graph we wish to find a linear ordering of the vertices that minimizes some worst case objective over the natural cuts in the ordering; which separate an initial segment of the vertices from the rest. A prototypical problem here is cutwidth, where we want to minimize the maximum number of edges crossing a cut. The only known algorithm here is by [Leighton-Rao J.ACM 99] based on recursively partitioning ...
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Theory Seminar: Almost Logarithmic Approximation for Cutwidth and Pathwidth
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Dor Katzelnick (Technion)
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Wednesday, 31.01.2024, 12:15
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Taub 201
We study several graph layout problems with a min max objective. Here, given a graph we wish to find a linear ordering of the vertices that minimizes some worst case objective over the natural cuts in the ordering; which separate an initial segment of the vertices from the rest. A prototypical problem here is cutwidth, where we want to minimize the maximum number of edges crossing a cut. The only known algorithm here is by [Leighton-Rao J.ACM 99] based on recursively partitioning ...
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ceClub: Challenges and Opportunities In Securing Software Supply Chains
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Dr. Yaniv David (Columbia University)
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Wednesday, 31.01.2024, 11:30
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Meyer 861
Racing to be first to market and deploy new features, developers rely on many external libraries to underpin their software. Each library uses more libraries, creating vast networks of dependencies that the developers know little about and have no control over, forming a knowledge gap that quickly turns into technical debt. Repaying this debt is difficult, as analyzing or examining all libraries is infeasible, and worse, the debt keeps growing due to frequent library updates. Atta...
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CS Lecture: On Implicit Bias and Benign Overfitting in Neural Networks
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Gal Vardi
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Wednesday, 31.01.2024, 10:30
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Taub 601
When training large neural networks, there are typically many solutions that perfectly fit the training data. Nevertheless, gradient-based methods often have a tendency to reach those which generalize well, namely, perform well also on test data. Thus, the training algorithm seems to be implicitly biased towards certain networks, which exhibit good generalization performance. Understanding this “implicit bias” has been a subject of extensive research recently. Moreover, in con...
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Diffusion Lens: Interpreting Text Encoders in Text-to-Image Pipelines
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Michael Toker
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Monday, 29.01.2024, 15:30
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Taub 601
Text-to-image diffusion models (T2I) use a latent representation of a text prompt to guide the image generation process. However, the encoder that produces the text representation is largely unexplored. We propose the Diffusion Lens, a method for analyzing the text encoder of T2I models by generating images from its intermediate representations. Using the Diffusion Lens, we perform an extensive analysis of two recent T2I models.We find that the text encoder gradually build...
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CS Lecture: Verification of Complex Hyperproperties
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Hadar Frenkel
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Sunday, 28.01.2024, 10:30
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Auditorium 012, floor 0
Hyperproperties are system properties that relate multiple execution traces to one another. Hyperproperties are essential to express a wide range of system requirements such as information flow and security policies; epistemic properties like knowledge in multi-agent systems; fairness; and robustness. With the aim of verifying program correctness, the two major challenges are (1) providing a specification language that can precisely express the desired properties; and (2) providin...
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Theory Seminar: The Sample Complexity Of ERMs In Stochastic Convex Optimization
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Daniel Carmon (Technion)
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Wednesday, 24.01.2024, 12:15
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Taub 201
Stochastic convex optimization is one of the most well-studied models for learning in modern machine learning. Nevertheless, a central fundamental question in this setup remained unresolved: How many data points must be observed so that any empirical risk minimizer (ERM) shows good performance on the true population? This question was proposed by Feldman who proved that Ω(\frac{d}{ϵ} + \frac{1}{ϵ^2}) data points are necessary (where d is the dimension and ε > 0 is the accurac...
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The Technion CTF Team opens at the Faculty
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Tuesday, 23.01.2024, 18:30
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Taub 9
The Technion CTF Team opens at the Faculty We invite you to join the Capture The Flag - CTF meetings. CTF is a cyber challenge competition and information security on the topics: cryptography, reverse engineering, forensics, web, etc. The meetings will include guest lectures and practical experience in solving challenges. Beginner and experienced students are welcome to join. The first introductory meeting will be held on Tuesday, January 23 at 6:30 pm at Taub 9. In the f...
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CGGC Seminar: Poisson Manifold Reconstruction (beyond co-dimension one)
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Prof. Misha Kazhdan (Computer Science, Johns Hopkins University)
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Thursday, 18.01.2024, 11:30
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Taub 012 (Learning Center Auditorium)
In this talk we consider the problem of manifold reconstruction from oriented point clouds for embedded manifolds of co-dimension larger than one. Using the framework of Poisson Surface Reconstruction, and formulating the problem in the language of alternating products, we show that the earlier approach for reconstructing hyper-surfaces extends to general manifolds, at the cost of replacing a quadratic energy with a multi-quadratic energy. We provide an efficient iterative hierarc...
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Theory Seminar: Online edge coloring
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David Wajc (Technion)
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Wednesday, 17.01.2024, 12:15
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Taub 201
Vizing’s Theorem provides an algorithm that edge colors any graph of maximum degree Δ using Δ+1 colors, which is necessary for some graphs, and at most one higher than necessary for any graph. In online settings, the trivial greedy algorithm requires 2Δ-1 colors, and Bar-Noy, Motwani and Naor in the early 90s showed that this is best possible, at least in the low-degree regime. In contrast, they conjectured that for graphs of superlogarithmic-in-n maximum degree, much better ...
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Internet-Scale Consensus in the Blockchain Era
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Joachim Neu
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Tuesday, 16.01.2024, 11:00
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Taub 601
Blockchains have ignited interest in Internet-scale consensus as a vital building block for decentralized applications and services that promise egalitarian access and robustness to faults and abuse. While the study of consensus has a 40+ year tradition, the new Internet-scale setting requires a fundamental rethinking of models, desiderata, and protocols. An emergent key challenge is to simultaneously serve clients with different requirements regarding the two fundamental aspects ...
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12-Lead ECG Classification Using Deep Learning Methods
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Vadim Gliner
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Thursday, 04.01.2024, 12:30
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Faculty of Biomedical Engineering, Silver Building, Room 201
12-lead electrocardiogram (ECG) recordings can be collected in any clinic and the interpretation is performed by a clinician. Modern machine learning tools may make them automatable. However, a large fraction of 12-lead ECG data is still available in printed paper or image only and comes in various formats. To digitize the data, smartphone cameras can be used. Nevertheless, this approach may introduce various artifacts and occlusions into the obtained images.Here, I will p...
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CS Lecture: Learning From Dependent Data And Its Modeling Through The Ising Model
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Yuval Dagan
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Monday, 01.01.2024, 10:30
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Auditorium 012, floor 0
I will present a theoretical framework for analyzing learning algorithms which rely on dependent, rather than independent, observations. While a common assumption is that the learning algorithm receives independent datapoints, such as unrelated images or texts, this assumption often does not hold. An example is data on opinions across a social network, where opinions of related people are often correlated, for example as a consequence of their interactions. I will present a line o...
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