Early Time Classification with Accumulated Accuracy Gap Control

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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CS RESEARCH DAY 2024

Wednesday, 03.04.2024, 12:30

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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Stable Tuple Embeddings for Dynamic Databases

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

Wednesday, 28.02.2024, 12:30

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

Sarel Cohen (Tel-Aviv Academic College)

Wednesday, 28.02.2024, 12:15

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

Naama Ben-David, Technion

Monday, 26.02.2024, 13:30

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

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

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

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

Gal Arnon (Weizmann institute)

Wednesday, 21.02.2024, 12:15

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

Yuval Gil, Technion

Monday, 19.02.2024, 13:30

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

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

Idan Mehalel (Technion)

Wednesday, 14.02.2024, 12:15

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

Ron Marcus

Wednesday, 14.02.2024, 11:30

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

Tuesday, 13.02.2024, 18:30

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

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

Wednesday, 07.02.2024, 12:30

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

Konstantin Zabaranyi (Technion)

Wednesday, 07.02.2024, 12:15

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

Tuesday, 06.02.2024, 18:30

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

Elad Kinsbruner

Tuesday, 06.02.2024, 12:30

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

Guy Gaziv (DiCarlo Lab at MIT)

Tuesday, 06.02.2024, 11:30

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

Gilad Asharov (Bar Ilan University)

Thursday, 01.02.2024, 11:30

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

Dor Katzelnick

Wednesday, 31.01.2024, 12:30

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

Dor Katzelnick (Technion)

Wednesday, 31.01.2024, 12:15

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

Dr. Yaniv David (Columbia University)

Wednesday, 31.01.2024, 11:30

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

Gal Vardi

Wednesday, 31.01.2024, 10:30

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

Michael Toker

Monday, 29.01.2024, 15:30

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

Hadar Frenkel

Sunday, 28.01.2024, 10:30

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

Daniel Carmon (Technion)

Wednesday, 24.01.2024, 12:15

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

Tuesday, 23.01.2024, 18:30

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)

Prof. Misha Kazhdan (Computer Science, Johns Hopkins University)

Thursday, 18.01.2024, 11:30

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

David Wajc (Technion)

Wednesday, 17.01.2024, 12:15

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

Joachim Neu

Tuesday, 16.01.2024, 11:00

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

Vadim Gliner

Thursday, 04.01.2024, 12:30

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

Yuval Dagan

Monday, 01.01.2024, 10:30

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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