The Taub Faculty of Computer Science Events and Talks

Over the past two decades, advancements in gene expression laboratory methods have brought about a level of maturity that allows for the routine examination of gene expression at both the single-cell level and spatially across tissues. However, existing data analysis methods in single-cell sequencing predominantly concentrate on identifying cell clusters or delineating the principal progression line within the data. Spatial transcriptomics analysis primarily focuses on clustering ...
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In meta reinforcement learning (meta-RL) an agent seeks an optimal policy when facing a new unseen task that is sampled from a known task distribution. Such a policy leads an effective trade-off between information gathering and reward accumulation. The offline variant of meta-RL (OMRL) presents a challenge to learn such a policy, as previous work established an identifiability problem in OMRL termed MDP ambiguity. This problem relates to the difficulty of learning a neural networ...
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Programmable switches enable offloading various network functions, such as anomaly detection and traffic engineering, to the same switches that perform packet routing. A basic component in many such applications is detecting heavy hitters (largest flows).Realizing such data plane algorithms requires taking into consideration all types of limited hardware resources of the switch, including the recirculation bandwidth, number of stages, and memory. This motivates solutions t...
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Recent years have witnessed remarkable advancements in generative models within the realm of computer vision. However, while great progress has been made in implicitgenerative techniques (e.g. GANs and Diffusion Models), methods that explicitly model the data distribution have been significantly lagging behind. This seminar will present our research on such methods, which are collectively known as Energy-Based Models (EBMs). I will start by revisiting the classical Contrastive Div...
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Our research focuses on new techniques for homomorphic secret sharing (HSS) which is a promising new cryptographic tool for privacy-preserving computations. HSS can be seen as a relaxation of fully homomorphic encryption (FHE), the latter being an encryption with the capability to perform calculations on encrypted data without decrypting first.FHE is a well-studied topic in cryptography that has recently attracted a lot of research both in academia and in the industry. How...
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In many realistic settings, a robot is tasked with grasping an object without knowing the object's exact pose. Instead, the robot relies on a probabilistic estimation of the object pose to decide how to attempt to grasp the object. We offer a novel measure, called Value of Assistance, or VOA, for assessing the expected effect a specific observation will have on the robot's ability to successfully grasp the object. VOA supports the decision of where and when it would be most benefi...
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You are invited to register for a first aid workshop that will be held at the faculty at the initiative of the student council. Tuesday 11/28 at 17:00, at the multi-purpose center in Taub. Pre-registration is required at the ...
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The Internet services which we enjoy in our day-to-day lives---search, social networking, online maps, video sharing, online shopping—run on Data Centers (DCs). DCs are warehouse scale computers that consist of tens of thousands of machines which are interconnected via fast networks. Building and maintaining DCs is tremendously expensive, for example, Amazon’s DC in Tel-Aviv spans over 100,000 square feet and they estimate that building each DC costs approximately 2.37 billion...
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On Wednesday, November 22, 2023, at 11:30 AM, we will gather to advocate for the release of the abductees. This event will be held at the Central Library Square.Due to the Home Front Command's regulations on public gatherings, registration is required to participate.Please register at the following link.Together, we stand strong!...
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Atrial fibrillation (AF) is the most prevalent form of heart arrhythmia and is associated with a fivefold increase in stroke incidence. In the context of AF detection, some patients experience sporadic AF events. This makes the Holter electrocardiogram (ECG) examination, which captures longer-term heart activity, essential to capture these irregular events. Automatic detection of AF in Holter recordings has the potential to reduce clinician workload. On the ECG, AF is characterize...
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Recent advances in interpretability research suggest we can project weights and hidden states of transformer-based language models (LMs) to their vocabulary, a transformation that makes them more human interpretable. In this paper, we investigate LM attention heads and memory values, the vectors the models dynamically create and recall while processing a given input. By analyzing the tokens they represent through this projection, we identify patterns in the information flow inside...
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This lecture is about our paper that was published in NeurIPS 2022. This paper deals with deep transductive learning, and proposes TransBoost as a procedure for fine-tuning any deep neural model to improve its performance on any (unlabeled) test set provided at training time. TransBoost is inspired by a large margin principle and is efficient and simple to use. Our method significantly improves the ImageNet classification performance on a wide range of architectures, such as ResNe...
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In the current period, we invite you to "eye-level" scientific intermission lectures especially for you. The lectures will be delivered online by our faculty members. The first lecture: "Information storage systems: past, present and back to the future" Prof. Eitan Yaakobi Wednesday 11/15 at 11:00 waiting for you!!...
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At the heart of our research lies a simple yet profound question: how can we bridge the gap between different visual, geometric, and language modalities? Firstly, we address the task of aligning colored point clouds embedded in 3D, obtained by a colored depth scanner, with color images provided by conventional cameras. These two data forms are inherently different, in both structural and chromatic properties. We use a tailored optimization procedure to align the point cloud and ca...
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Recent years have witnessed remarkable advancements in generative models within the realm of computer vision. However, while great progress has been made in implicit generative techniques (e.g. GANs and Diffusion Models), methods that explicitly model the data distribution have been significantly lagging behind. This seminar will present our research on such methods, which are collectively known as Energy-Based Models (EBMs). I will start by revisiting the classical Contrastive Di...
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We study the design of coding schemes for blockchain networks, focusing on state organization and memory-efficient data structures for communication protocols. We first propose traffic-aware sharding, a technique that arranges data into distinct groups, to decrease overhead from cross-shard transactions while providing memory-efficient mappings of data into shards. Then, we study the use of Merkle trees in transaction proof verification, discussing a traffic-aware approach to orga...
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Local explanation methods highlight the input tokens that have a considerable impact on the outcome of classifying the document at hand. For example, the Anchor algorithm applies a statistical analysis of the sensitivity of the classifier to changes in the token. Aggregating local explanations over a dataset provides a global explanation of the model. Such aggregation aims to detect words with the most impact, giving valuable insights about the model, like what it has learned in t...
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The hierarchical clustering problem deals with the construction of an M-layer hierarchical partition of a given graph. Every pair of vertices in the graph is associated with a layer. The objective is to construct a hierarchical partition that separates vertices as close as possible to their associated layer. It is proven that any approximation algorithm for this problem, induces an approximation algorithm of the same factor, for the problem of fitting tree metrics to general data,...
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Determining the size of a concurrent data structure correctly and efficiently in the presence of concurrent modifications has turned out to be a surprisingly difficult task, one that has been absent from both research and practical applications until recently. In this work, we study three methodologies for concurrently computing a linearizable size, with the aim of improving performance. In our first approach, we employ the handshake methodology used by on-the-fly garbage collecto...
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Range matching plays a crucial role in computer systems, including networking, security, and storage. It serves the purpose of locating a range that encompasses a given input number from a vast collection of ranges. Address translators in operating systems and longest-prefix matching in networks heavily rely on range matching. However, existing range matching algorithms are limited in scalability and performance due to their reliance on pointer-chasing techniques.We introd...
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This research is centered around the application of machine learning approaches to domains in which training labels are prohibitively expensive to obtain or training data in general are impossible to procure.Initially, the study focused on investigating weak supervision in medical applications, in which data labelling is extremely expensive; specifically showcasing how a restricted number of high-quality labels can significantly improve algorithm performance in diagnosing ...
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Tracing garbage collectors are widely deployed in modern programming languages. But tracing an arbitrary heap shape incurs poor locality and may hinder scalability. In this paper, we explore an avenue for mitigating these inefficiencies at the expense of conservative, less accurate identification of live objects. We do this by proposing and studying an alternative to the Mark-Sweep tracing algorithm, called Linear-Mark. It turns out that although Linear-Mark improves locality and ...
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We introduce a new family of clustering problems, which we denote by Hyper Correlation Clustering, that takes into account higher-order structures. Our new family captures multiple classic graph cut problems, e.g., Min s-t Cut, Multiway Cut, and Multicut, in addition to disagreement minimization on general weighted graphs in Correlation Clustering, as well as other studied hypergraph clustering problems.In Hyper Correlation Clustering we are given a hypergraph H=(V,E) whos...
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In-Network Computing is a concept of acceleration of applications by offloading some computation to run on network devices. Recently enabled by the emergence of data-plane programmable PISA switches, in-network computing was shown to offer dramatic performance boosts in a variety of applications such as load balancers, coordination protocols, aggregation and more. However, existing switches lack the essential support for multitenancy, limiting the benefits only to data center oper...
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Glaucoma is a group of eye diseases that gradually leads to peripheral vision loss and blindness. It is affecting about 90 million people worldwide and usually painless. Glaucoma has no cure and it advances moderately if not treated on time. Therefore early and fast diagnosis is crucial for effective treatment. In this work I examine to what extent inferior retinal images affects glaucoma diagnosis. Then I develop a Retinal Image Quality Assessment (RIQA) system accordingly, to sc...
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Deep Neural Networks (DNNs) are highly sensitive to imperceptible malicious perturbations, known as adversarial attacks. Following the discovery of this vulnerability in real-world imaging and vision applications, the associated safety concerns have attracted vast research attention, and many defense techniques have been developed. Most of these defense methods rely on adversarial training (AT) -- training the classification network on images perturbed according to a specific thre...
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The script theory in psychology suggests that cognitive scripts, sequences of expected actions in commonly encountered situations, play a significant role in shaping our comprehension of the world. The concept of scripts was utilized in artificial intelligence in its early days, serving as a tool for representing procedural knowledge and enhancing story understanding. Script-based methods, like the Script Applier Mechanism (SAM), marked a significant advancement in AI, but their r...
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We study the classic problem of online weighted paging with a probabilistic prediction model, in which we are given additional information about the input in the form of distributions overpage requests, known as distributional online paging (DOP). Our main result is an efficient online algorithm that achieves a constant factor competitive ratio with respect to the best online algorithm (policy) for weighted DOP.Our starting point is a linear programming formulation for we...
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We study the uniform 2-dimensional vector multiple knapsack (2VMK) problem, a natural variant of multiple knapsack arising in real-world applications such as virtual machine placement. The input for 2VMK is a set of items, each associated with a 2-dimensional weight vector and a positive profit, along with m 2-dimensional bins of uniform (unit) capacity in each dimension. The goal is to find an assignment of a subset of the items to the bins, such that the total weight of items as...
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We propose PB-FS (Postcard-Based Fast Start), a rate initialization scheme that uses direct feedback from the switches to quickly correct the rates of new datacenter flows that begin at the line rate and cause congestion. PB-FS is designed to easily integrate into any datacenter congestion control protocol. We evaluate PB-FS in two datacenter environments: a lossless network that runs RoCE, and a lossy network that uses RDMA with selective repeat. We show that PB-FS significantly ...
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  To participate, register at the linkIn the program:Dr. Inbal Tsafir-Lavia, CEO and co-entrepreneur at Nevia Bio, which is developing a test for the early diagnosis of ovarian cancerMichal Shanhav, Talent Acquisi...
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Cooperative Multi-Agent teams can be deployed in many interesting and important domains such as industry, transportation, agriculture, security and more. In this talk, I will introduce key results from my research, primarily focusing on theoretical work concerned with search for smart agents by UAV teams. Suppose that in a given planar circular region, there are some smart mobile agents, and we would like to find them using teams of sweeping agents. A smart agent is an agent capab...
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The rich physics present in a wide range of spintronic materials and devices provide opportunities for a variety of computing applications. This presentation will describe six distinct proposals to leverage spintronic phenomena for reversible computing, neuromorphic computing, reservoir computing, and hardware security. The presentation will begin with a solution for reversible computing in which magnetic skyrmions propagate and interact in a scalable system with the potential for...
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The proliferation of modern mobile phones has opened up unprecedented opportunities for leveraging location-tracking capabilities to extract individual mobility patterns and contextual information. However, existing approaches heavily rely on analyzing geolocation data obtained from Global Navigation Satellite System (GNSS) observations, which are limited when used in enclosed spaces. This talk presents new algorithms for efficient mobility data analysis and contextual learning by...
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Denoising Diffusion Probabilistic Models (DDPM), also known as diffusion models, have recently emerged as state-of-the-art generative models, synthesizing images with unprecedented quality and realism. At their core, diffusion models employ an MSE-trained denoiser neural network in an iterative scheme, transforming random noise into pristine images. Theoretically, this algorithm is proven to draw samples from a learned prior image distribution. In our work, we adapt pre-trained di...
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Digital analysis of pathology whole-slide images is fast becoming a game changer in cancer diagnosis and treatment. Specifically, deep learning methods have shown great potential to support pathology analysis, with recent studies identifying molecular traits that were not previously recognized in pathology H&E whole-slide images. Simultaneous to these developments, it is becoming increasingly evident that tumor heterogeneity is an important determinant of cancer prognosis and susc...
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A critical notion in coding theory is that of a good code—a code with constant rate and distance. A natural analogous notion in the p-norm (1 <= p <= 2) is that of a good l_p-spread subspace. A linear subspace C \subset R^n is called good l_p-spread if dim(C) >= Omega(n) "constant rate"), and every x \in C \ {0} is at least Omega(|x|_p)-far (in l_p-distance)&nb...
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Real-time systems are designed to respond to external stimuli and complete tasks within a predetermined timeframe. The development of these systems often involves the use of cycle-accurate simulation environments and digital twin systems to accurately model the system and its operating environment. Ensuring high reliability and security in real-time systems is essential, and the development environment must incorporate events related to reliability, such as sensor failure and subs...
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Deep Neural Networks (DNNs) training continues to scale over size and computational footprint, as a result of a higher number of trainable parameters, wider and deeper models, and growing amounts of training data. As improvements in model quality lead over hardware capabilities, this scale-up translates into a need for a growing number of training devices working in tandem, turning distributed training into the standard approach for training DNNs on a large scale. This seminar del...
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One of the prominent methods for explaining the decision of a machine-learning classifier is by a counterfactual example. Most current algorithms for generating such examples in the textual domain are based on generative language models. Generative models, however, are trained to minimize a specific loss function in order to fulfill certain requirements for the generated texts. Any change in the requirements may necessitate costly retraining, thus potentially limiting their appl...
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You are invited to the Finals event of the Best Project Competition, which will be held in the format of a project fair, and everyone is invited to encourage the competing teams and watch the most creative projects. The event will take place on Wednesday, June 28, 2023 on the entrance floor of the Taub Computer Science Building: 12:30 - Project fair in the CS lobby of the Taub Building - entrance floor 14:00 - Announcement of the winners and awarding of certificates and prizes in...
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We prove a few new lower bounds on the randomized competitive ratio for the $k$-server problem and other related problems, resolving some long-standing conjectures. In particular, for metrical task systems (MTS) we asympotically settle the competitive ratio and obtain the first improvement to an existential lower bound since the introduction of the model 35 years ago (in 1987). More concretely, we show: 1. There exist $(k+1)$-point metric spaces in which the randomized competit...
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Directional and vector fields are central objects in geometry processing. They are commonly represented with low-order simple elements on watertight surfaces in FEM and in computer graphics, for simplicity and sparsity. Moreover, they are classically defined only on conventional symmetries. I will discuss some recent works of extending these classical representations with alternative bases, where then important tasks in downstream applications like meshing, computations of flows, ...
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When multiple programs execute on the same computer, they share the use of the microarchitectural resources. Because program execution affects the state of the microarchitecture and the state of the microarchitecture affects program execution time, measuring execution time can reveal information on the state of the microarchitecture, and with it on prior execution of other programs. Thus, such micoroarchitectural timing attacks leak information by measuring variations in program e...
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You are invited to the CS Projects Fair for the Spring Semester of 2023, where 30 teams of undergraduate students will present and demonstrate projects in various fields in IoT, Android, Arduino and Networks, developed as part of the final project in the software engineering and communication networks track, most of which were carried out in collaboration with various social associations and organizations, and were intended to make a contribution to the community. The fair will b...
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Humans can ubiquitously communicate and reason about both tangible and abstract shape properties. Artists can succinctly convey complex shapes to a broad audience using a range of mediums; and human observers can effortlessly analyze and agree on observed shape properties such as upright-orientation or style. While perception research provides some clues as to the mental processes humans employ when performing these tasks, concrete and quantifiable explanations of these actions ar...
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Light-field cameras promised to revolutionize imaging by capturing and recording the propagation paths of light-rays through space. This light-field information, equivalent to canonical optical phase space, supposedly holds the “sys-admin” password to optical imaging. Digital post-processing and manipulation can allow digital refocusing of rays, correction of optical aberrations, as well as calculating the distance to every point in the imaged scene. However, once this technol...
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A central task in social choice is that of aggregating voter preferences to decide who wins. For this task, a voting rule maps a collection of voter preferences over the candidates to a set of winning candidates. Relevant scenarios may be political elections, document rankings in search engines, hiring dynamics in the job market, and so on. We study situations in which voter preferences are incomplete. These scenarios arise naturally in a variety of practical settings: voters may ...
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This talk will discuss our recent advancements in recycling finetuned models and collaborative pretraining. We would describe how to harness the data and computation invested in one or more models to collaboratively improve the pre-trained model they originated from, once or over and over again. The work will also touch on our initial understanding of how and why fusing several models by weight averaging works. All of these are small steps towards evolving pretrained models that w...
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In this talk, we will review the various needs and solutions for storage in HPC environments. We will compare the requirements for storage when used for data input and output, scratch space, or inter-server communication, and review the various solutions for them, When reviewing solutions, we will analyze the various access protocols, technologies and specific solutions. We will also compare on-prem storage solutions to cloud-based ones, Bio: Dr. Omri Palmon has a Ph.D. in comput...
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A distribution is k-incompressible, Yao [FOCS ’82], if no efficient compression scheme compresses it to less than k bits. While being a natural measure, its relation to other computational analogs of entropy such as pseudoentropy, Hastad, Impagliazzo, Levin, and Luby [SICOMP 99], and to other cryptographic hardness assumptions, was unclear. We advance towards a better understating of this notion, showing that a k-incompressible distribution has (k-2) bits of next-block pseudoen...
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In this talk I will describe how to plant novel types of backdoors in any facial recognition model based on the popular architecture of deep Siamese neural networks, by mathematically changing a small fraction of its weights (i.e., without using any additional training or optimization). These backdoors force the system to err only on specific persons which are preselected by the attacker. For example, we show how such a backdoored system can take any two images of a particular per...
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Repeat-free codes are used to ensure unique reconstruction from fragmentation, assuming full (uniform) read-coverage of substrings, with applications to DNA-based storage systems. In this talk, we explore a generalization aimed at resilience to pre-fragmentation noise, and study existence results as well as explicit constructions. Yonatan Yehezkeally is the Carl Friedrich von Siemens post-doctoral research fellow of the Alexander von Humboldt Foundation, in the Associate Professo...
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DNA labeling is a powerful tool in molecular biology and biotechnology that allows for the visualization, detection, and study of DNA at the molecular level. Under this paradigm, a DNA molecule is being labeled by specific k patterns and is then imaged. Then, the resulted image is modeled as a (k + 1)-ary sequence in which any non-zero symbol indicates on the appearance of the corresponding label in the DNA molecule. The primary goal of this work is to study the labeling capacity,...
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The All-Pairs Shortest Paths (APSP) problem is one of the most fundamental problems in graph algorithms. It is well-known that APSP can be solved in O(n^3) time in weighted graphs, and in O(n^{omega}) time in unweighted graphs, where omega...
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Terrain-aided navigation (TAN) was developed before the GPS era to prevent the error growth of inertial navigation. TAN algorithms were initially developed to exploit altitude over ground or clearance measurements from a radar altimeter in combination with a Digital Terrain Map (DTM). After almost two decades of silence, the availability of inexpensive cameras and computational power and the need to find efficient GPS-denied positioning solutions have prompted a renewed interest i...
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Over the course of four decades, the academic field of computer science transformed from a branch of mathematics to a key driver of the evolution of our species. Graduates of academic computer science programs today routinely create systems that would have been considered, just a century ago, miracles of mythic proportions. Judging by cultural impact, computer science departments today resemble Hogwarts much more than they resemble the theoretical havens they used to be before c...
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CS Special Guest Lecture by Prof. Avi Wigderson, IAS Princeton, on the Occasion of his Being Awarded an Honorary Doctorate from the Technion Recently, a group of theoretical computer scientists posted a paper on the Arxiv with the strange-looking title "MIP* = RE", surprising and impacting not only complexity theory but also some areas of math and physics. Specifically, it resolved, in the negative, the "Connes' embedding conjecture" in the area of von-Neumann algebras, and the "...
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When users can benefit from certain predictive outcomes, they may be prone to act to achieve those outcome, e.g., by strategically modifying their features. The goal in strategic classification is therefore to train predictive models that are robust to such behavior. However, the conventional framework assumes that changing features does not change actual outcomes, which depicts users as "gaming" the system. Here we remove this assumption, and study learning in a causal strategic ...
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In recent years, extensive research has been dedicated to the development of nano- and micro-machines. While the majority of practical research is focused on chemistry and biology, there is also research aimed at communication aspects. This is crucial because nano-machines are limited in their capabilities and require communication and networking to tackle complex tasks. By collaborating, these machines can revolutionize medicine by serving as intelligent drug delivery systems, ad...
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Out of necessity C++ has been an evolving language. I outline some early ideals for C++, some techniques for keeping the evolution directed, and show how C++20 comes close to many of those ideals. Specific topics include type-and-resource safe code, generic programming, modularity, the elimination of the preprocessor, and error handling. Naturally, over the years, C++ has acquired many “barnacles” that can become obstacles to developing elegant and efficient code. That has b...
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Levenshtein's reconstruction model was first introduced in 2001 and suggests transmitting a word over multiple noisy channels, then using the channels' outputs to recover the transmitted word. This talk will discuss the reconstruction model when the channels are prone to combinations of errors, or when unique retrieval of the transmitted word is not guaranteed to succeed. In particular, when the channels introduce a limited number of insertions (or deletions), and unique decoding ...
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Why hybrid and what problems this technology solves? What is the difference between Intel’s Hybrid Technology and the other market solutions (e.g. Big-little)? Hybrid micro-architectural solutions: caches, fabric. How SW knows what core to use for what task. Intel Thread Director - what is does and why it is required. Future development of Hybrid solutions. Bio: Yuli (Julius) Mandelblat is an Intel Fellow of Client SoC Architecture Team. Yuli works at Intel since 1990. Through...
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Mobile robotic agents often suffer from localization uncertainty which grows with time and with the agents' movement. This can hinder their ability to accomplish their task. In some settings, it may be possible to perform assistive actions that reduce uncertainty about a robot’s location. Since assistance may be costly and limited, and may be requested by different members of a team, there is a need for principled ways to support the decision of which assistance to provide to an...
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One of the key components in PCP constructions are agreement tests. In agreement testing the tester is given access to subsets of fixed size of some set, each equipped with an assignment. The tester is then tasked with testing whether these local assignments agree with some global assignment over the entire set. One natural generalization of this concept is the case where, instead of a single assignment to each local view, the tester is given access to $\ell$ different assignme...
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Many datasets in real life are complex and dynamic, that is, their key densities are varied over the whole key space and their key distributions change over time. It is challenging for an index structure to efficiently support all key operations for data management, in particular, search, insert, and scan, for such dynamic datasets. In this talk, I will present DyTIS (Dynamic dataset Targeted Index Structure), an index that targets dynamic datasets. DyTIS, though based on the stru...
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You are invited to the research meeting - NLP Research Night (in collaboration with Grove Ventures - round tables with senior researchers from academia and industry in an open dialogue about the topics,...
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You are invited to participate in the international conference SYSTOR 2023, leader in the fields of systems, cloud and storage, which will be held this year for the first time at the Technion, on Monday-Wednesday, June 5-7, 2023, at the Technion Samuel Neaman Institute for National Policy. Participation is free of charge but requires pre-registration. ...
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Substantial efforts have been devoted into improving the capabilities of neural networks to solve algorithmic tasks. Through training, these networks learn to mimic algorithmic behaviour, enabling them to handle tasks such as sorting, navigating, and managing complex data structures like graphs. However, classic algorithms and neural networks are fundamentally different, making it challenging to analyze the complexity of an algorithm learned by a neural network. First, it is neces...
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You are invited to the "Research on the Bar" evening - TED lectures and a meeting with three faculty members and their research groups on Wednesday, May 31, 2023 at 19:00 pm in Taub Terrace: Prof. Eitan Yacobi: Storing information in DNA: Who ate my files? Dr. Shaul Almagor: How to never make a mistake in anything Dr. Ron Rothblum: How to prove without revealing anything Please pre-register....
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The increasing demand for data storage has prompted the exploration of new techniques, with molecular data storage being a promising alternative. The stored information can be represented as a collection of two-dimensional arrays, such that each row represents a DNA strand. In this work, we present the results of our research into error-correcting codes for molecular data storage using this representation. Although both insertions and deletions have been observed to occur, the foc...
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The virtual memory subsystem translates the address of each memory reference from its virtual to its physical representation, increasing execution runtimes by as much as 50% and 90% in bare-metal and virtual setups, respectively. We alleviate these overheads by developing improved virtual memory designs: (i) hashed page tables and (ii) TLB partitioning for simultaneous multithreading. We additionally develop an efficient and reliable methodology for evaluating the performance of n...
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You are invited to recruitment day by CYE with engineers and recruitment teams and to a technological lecture by Dr. Nimrod Partosh, CS graduate and VP of AI at the company, which will deal with the question: How do you quantify the chance of a cyber attack in real organizations (and what do you do when the problem is NP-hard)? - on Wednesday, May 31, 2023 at 12:30 in the Taub lobby, and the lecture will take place at 13:30 in the Taub 012 Auditorium in the Learning Center on the ...
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In this talk we consider the following adversarial, non-Markovian, random walk on “good enough” expanders: Starting from some fixed vertex, walk according to the instructions X = X1,…,Xt, where each Xi is only somewhat close to having only little entropy, conditioned on any prefix. The Xi-s are not independent, meaning that the distribution of the next step depends not only on the walk’s current node, but also on the path it took to get there. We show that such walks (or ...
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You are invited to Intel's Tech Experience event, on Tuesday, May 30, 2023, on the "Shany" Plaza of Taub Building: Between 9:00-12:00 - AR/VR complex Between 12:00-13:30 / 13:30-15:00 - two rounds of the FPGA workshop Hello world More details, full program and pre-registration ...
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This talk is about distributed machine learning in the presence of Byzantine errors. A main node performs gradient descent steps with the help of some worker nodes, a limited number of which are controlled by an adversary. These malicious worker nodes can return arbitrary data to the main node instead of the desired computation results. Prior work proposes distributing the data with redundancy among the workers and using error correction codes to detect and correct the erroneous c...
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Drug development is a long and costly process consisting of several stages that can take many years to complete. One of the early stage's goals is to optimize a novel chemical compound to be active against a target protein associated with the disease. The goal of molecule optimization is, given an input molecule, to produce a new molecule that is chemically similar to the input molecule but with an improved property. In this work, we present a novel approach for optimizing m...
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You are invited to celebrate 30 years of excellence: the Technion program for excellence is celebrating 30 years since its establishment in a series of lectures, on Wednesday, May 24, 2023 between 13:00-17:00, in Taub Auditorium 1, by program graduates and experts from academia and industry who will talk about their experience and insights on the trends, The latest innovations and challenges in their field. Among the speakers: Prof. Ado Kaminer, Dr. Kira Radinsky, Prof. Nadav Coh...
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I will discuss a new approach towards constructing good locally testable codes (LTCs) with better qualities than the recent constructions of good LTCs. This approach continues the trend of using high dimensional expanders (HDXs) for constructing LTCs, but introduces a new ingredient: a sheaf on the HDX at hand. We show that if one could find a single example of a sheaved HDX satisfying some local expansion conditions and a cohomological condition --- both of which can be checked i...
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The UW-Madison Center for High Throughput Computing (CHTC) is the home of the HTCondor Software Suite (HTCSS). Located in the Computer Sciences department, the center was established more than 15 years ago on the foundation of a research methodology that brings together innovation in distributed computing and services to scientists. Evaluation of new technologies under real-life conditions by engaged users advanced scientific discovery and guided the center in future research and ...
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The general synchronization problem asks to recover states of objects from their corrupted relative measurements. When the states are represented by group elements (e.g. 3-D rotations or permutations) this problem is known as group synchronization. In several applications, the algebraic structure of the states is more complicated, for example, the states can be represented by partial permutations. The synchronization problem has many applications, in particular, to structure-from-...
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Machine learning model training is a computationally expensive task that requires significant amounts of time and resources, especially for larger models. The problem is further increased when data arrives in a continuous stream since the model must be retrained multiple times to incorporate the new data and ensure the model remains accurate. Another difficulty arises during inference time when the data is geo-distributed; centralizing all data updates can be costly and lead to ne...
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You are invited to a round tables event with Intel researchers on the world of validation and how to deal with validation challenges using AI, on Tuesday, May 16, 2023, 17:30 in Taub 337. Please pre-register....
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From carefully crafted quantum algorithms to information-theoretic security in cryptography, a quantum computer can achieve impressive feats with no classical analogue. Can their correct realization be verified? When the power of the device greatly surpasses that of the user, computationally as well as cryptographically, what means of control remain available to the user? Recent lines of work in quantum cryptography and complexity develop approaches to this question based on the n...
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Istra Research will hold a recruitment day and lecture on Wednesday, May 17, 2023, from 12:30-2:30 at the Taub Lobby, and at 13:00. there will be a lecture on Taub 3 (entrance floor) on "Introduction to Algorithm Trading" - High Frequency Trading - that you review basic concepts in the field. Pl...
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Anomaly detection aims to discover data which differ from the norm in a semantically meaningful manner. The task is difficult as anomalies are rare and unexpected. Moreover, a sample can be an important anomaly to one person and an uninteresting statistical outlier to another. In this talk, I will first present how deep representations brought substantial gains for image anomaly detection and segmentation. Next, we will discuss the types of representations that are beneficial for...
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This seminar will be divided into two parts. In the first part, we will provide an introduction to DNA storage systems. This will include an overview of their biological and computational components, as well as a survey of the current technologies and emerging trends in the market landscape. In the second part, we will focus on a novel problem called the DNA coverage depth problem. Motivated by the high cost and latency associated with DNA sequencing, we aim to design coding sch...
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This work studies the problem of distributed runtime verification of linearizability for asynchronous concurrent implementations. It proposes an interactive model for distributed runtime verification and shows that it is impossible to verify at runtime this correctness condition for some common sequential objects such as queues, stacks, sets, priority queues, counters and the consensus problem. The impossibility captures informal arguments used in the past that argue distributed r...
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You are invited to an information gathering workshop CYE's Bug Bounty, led by Naftali Elazar, a cyber expert at CYE, and to hear about mapping the information gathering process as part of the process of identifying vulnerabilities in the organization, about tools and techniques for identifying organizational assets exposed to the Internet, and about gathering information using familiar tools and their use of the leading technologies in the market, on Wednesday, May 10, 2023, 18:30...
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Intuit - a global fintech company - will hold a recruitment day and will present its business in Trust Data & Deep Insight, its technology and products, as well as vacancies, on Wednesday, May 10, 2023 starting at 12:30 in the Taub lobby....
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More than twenty years ago, Capalbo, Reingold, Vadhan and Wigderson gave the first (and up to date only) explicit construction of a bipartite expander with almost full combinatorial expansion. The construction incorporates zig-zag ideas together with extractor technology, and is rather complicated. We give an alternative construction that builds upon recent constructions of hyper-regular, high-dimensional expanders. The new construction is, in our opinion, simple and elegant. Bey...
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You are invited to a Tech Talk by StarkWare, a company that develops STARK-based solutions in the blockchain industry, on blockchain, the Scale problem, and zero-knowledge proofs (zk proofs), on Sunday, May 9, 2023, 18:00, at the Junta Bar, Technion. Please pre-register....
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Robots sense, move and act in the physical world. It is therefore natural that understanding the geometry of the problem at hand is often key to devising an effective robotic solution. I will review several problems in robotics and automation in whose solution geometry plays a major role. These include designing optimized 3D printable fixtures, object rearrangement by robot arm manipulators, and efficient coordination of the motion of large teams of robots. As we shall see, exploi...
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In this talk, I will present two chapters from my Ph.D. thesis. The core of my research focuses on methods that utilize the power of modern neural networks not only for their conventional tasks such as prediction or reconstruction, but rather use the information they “learned” (usually in the forms of their gradients) in order to optimize some end-task, draw insight from the data, or even guide a generative model. The first part of the talk is dedicated to computational imagi...
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Existing storage technologies cannot keep up with the modern data explosion. There is a growing need to find alternatives for the current solutions for storing data. Storage systems based DNA, seems like an attractive possibility due to a number of unique properties of DNA mulecules, among them are that DNA is extremely dense (up to about 1 exabyte per cubic millimeter) and durable (half-life of over 500 years). A typical DNA storage system consists of three important component...
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Image and video denoising has been an area of research interest for decades. This talk will present three novel methods that take the denoising field a step forward. All the proposed methods in this work strongly rely on exploiting non-local self-similarity using patch matching. The first method, termed LIDIA [1], has two contributions. First, we propose a low-weight architecture that achieves near state-of-the-art performance. Our architecture relies on patch matching and separ...
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In this work, we study the complexity of computing the distance of a graph from being triangle-free in distributed settings, that is, computing the minimum number of edges that must be removed to achieve a graph without triangles. We present lower bounds for the exact solution showing that this task is “as hard as it gets”. We also show fast algorithms for approximate solutions in multiple distributed models....
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Detecting contradictions in text is essential in determining the validity of the literature and sources that we consume. Medical corpora are riddled with conflicting statements. This is due to the large throughput of new studies and the difficulty in replicating experiments, such as clinical trials. Detecting contradictions in this domain is hard since it requires clinical expertise. In this work, we present a distant supervision approach that leverages a medical ontology to build...
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You are invited to a designated meeting for graduate students, with a panel that will deal with research careers in industry: What does research in industry look like? What is the admission process for research positions? What are the types of jobs available and career paths? Featuring: Dr. Liane Levy-Eitan, Research Group Director, Amazon Amichai Shulman, cyber entrepreneur and investor Dr. Rachel Tzoref-Brill, Senior Researcher, IBM Research Laboratory The meeting will take pl...
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Balanced sequences and balanced codes have attracted a lot of research in the last seventy years due to their diverse applications in information theory as well as other areas of computer science and engineering. There have been some methods to classify balanced sequences. This work suggests two new different hierarchies to classify these sequences. The first one is based on the largest $\ell$ for which each $\ell$-tuple is contained the same amount of times in the sequence. This ...
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Quantum communication has seen rapid development in the last decade, in both practice and theory. Recently, there is a growing interest in how quantum entanglement can assist classical networks, i.e., non-quantum communication systems. In particular, there are known examples of classical multi-user channels such that the sum rate with entangled transmitters is strictly higher than the best achievable sum rate without such resources. The present work studies a two-user classical ...
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Abstract: Recently, large language models have been trained on intelligent languages including natural languages, such as English, and programming languages, such as Python. We will examine several interesting applications of these models. First, they can be used to enumerate human stereotypes and discriminatory biases, suggesting that they must be used carefully. Second, they can be used to generate and solve their own programming puzzles, which can be used in a self-training pip...
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You are invited to a joint lecture by the CS and EE on behalf of NVIDIA that will review AI and NVIDIA technologies, as well as the latest developments in the field of large language models, including effective tools for running large models, on Wednesday April 19, 2023 at 19:00, at the Faculty of Engineering Electrical, Auditorium 1003, Meyer Building. Please ...
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Technion CS open day 2023 invites outstanding undergraduates from all universities to learn about the Computer Science Department and register for Winter Semester 2023-24. The event will be held on Wednesday, April 19, 2022. between 12:30-14:00, room 337, Taub Building for Computer Science, Technion. The program will include review on curriculum, research and life at the Technion CS Department: - CS Dean, Prof. Danny Raz - Vice Dean, Prof. Gill Barequet - Dr. Liane Levy-Eitan, D...
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Public-key cryptography is the foundation for establishing secure communication between multiple parties. Traditional public-key algorithms such as RSA are based on the hardness of factoring large numbers or the discrete logarithm problem, but can be attacked in polynomial time once a capable quantum computer exists. Code-based public-key cryptosystems are considered to be post-quantum secure, but compared to RSA or elliptic curve cryptography their crucial drawback is the signifi...
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The translation lookaside buffer (``TLB’’) is a small cache that accelerates virtual to physical address translation, which processors typically manage with variants of the least recently used (``LRU’’) algorithm. Although LRU is simple, it is suboptimal for some workloads. Our analysis shows that if the processor uses the optimal---but impractical---Belady algorithm instead of LRU, runtime improves by up to 15% (and 5% on average) over LRU in single-thread (``ST’’) mo...
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You are invited to a meeting with hi-tech executives on "Democracy, Hi-tech and the Future Generation", with the participation of: Dr. Kira Radinsky Nadir Izrael Dr. Orna Berry Molly Aden Yoram Yaacovi Ori Hadomi Dr. YonathanYaniv Maor Farid Avner Rothschild On Monday, April 3, 2023, 17:30, in Taub 1. Please register in advance...
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The potential for machine learning to revolutionize scientific and engineering research is immense, but its transformative power cannot be fully harnessed through the use of off-the-shelf tools alone. To unlock this potential, novel methods are needed to integrate physical models and constraints into learning systems, accelerate simulations, and quantify model prediction uncertainty. In this presentation, we will explore the opportunities and emerging tools available to address th...
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We present connections between machine learning and theoretical computer science. In particular: hardness of data-set generation for deep learning problems and connections between randomness and computation in deep learning. ...
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You are invited to a practical testing workshop by CYE, supervised byTal Sihonov, director of the development group at the CYE, who will talk about the importance of tests in the industry and the world of development, with an emphasis on SaaS systems and will practice techniques of writing effective tests in Python, on Sunday, April 2, 2023 at 18:30, in Taub 337. Participating in the workshop requires prerequisite of completing the Introduction to Ssystems Programming course or ...
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You are invited to join the CS Hackathon-Doing Good programming competition, in collaboration with Ruth Rappaport Children's Hospital, Rambam Health Care Campus, to be held on Thursday-Friday, March30-31, 2023, at CS Taub Building, and which this year will find s...
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In the reliable transmission problem, a sender, Alice, wishes to transmit a bit-string x to a remote receiver, Bob, over a binary channel with adversarial noise. The solution to this problem is to encode x using an error-correcting code. As it is long known that the distance of binary codes is at most 1/2, reliable transmission is possible only if the channel corrupts (flips) at most a 1/4-fraction of the communicated bits. We revisit the reliable transmission problem in the two-...
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In image restoration, traditional supervised methods that seek to restore the source enjoy exceptional distortion performance but lack visual quality. With the emergence of powerful generative algorithms, many approaches focus on image realism and diversity, but forsake faithfulness to the source. Motivated by recent theoretical findings, we present a practical algorithm that optimizes source fidelity while aiming for photo-realistic results. Our method optimally transports the di...
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Proper X-ray radiation design (via dynamic fluence field modulation, FFM) allows reducing effective radiation dose in computed tomography without compromising image quality. It takes into account patient anatomy, radiation sensitivity of different organs and tissues, and location of regions of interest. We account for all these factors within a general convex optimization framework. Joint work with Anatoli Juditsky and Arkadi Nemirovski Short bio: Michael Zibulevsky received h...
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Amazon Research, Alexa Shopping 2023 Internship Program Introduction session will take place on Monday. March 27, 10:00-11:30 on Floor 2, CS Taub Building, and will present its research challenges and 2023 research internship program for graduate students in CS/EE/IEM: Program: 10:00-10:20 - Introduction to the 2023 internship program and Alexa Shopping domain overview, Liane Lewin-Eytan, Sr Mgr., Alexa Shopping, Amazon Presentation: “Alexa – Using AI to understa...
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In an Escape-room setting, we study different human behaviors when completing time-constrained tasks involving sequential decision-making and actions. We aim to construct a human mental model linking attention, episodic memory, and hand-object interaction. We record from two egocentric cameras: a head-mounted camera and Gaze-tracking glasses. We also record from up to four third-person cameras. Additionally, we created a detailed 3D map of the room. In this talk, I will discuss t...
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Given an undirected weighted graph, a distance oracle is a data structure that answers distance queries in the graph within a short time. A path-reporting distance oracle (PRDO) is a distance oracle that is also required to return a shortest path between the queried vertices. A particular interest is in oracles that have a linear storage size in the number of vertices of the input graph, and also have small query time and a good approximation factor (called the stretch). Througho...
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Layer-2 is a popular approach to deal with the scalability limitation of blockchain networks. It allows users to execute transactions without committing them to the blockchain by relying on predefined payment channels. Users together with the payment channels form a graph known as the offchain network topology. Transactions between pairs of users without a connecting channel are also supported through a path of multiple channels. Serving such transactions involves fees paid to int...
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In meta reinforcement learning (meta RL), an agent seeks a Bayes-optimal policy – the optimal policy when facing an unknown task that is sampled from some known task distribution. Previous approaches tackled this problem by inferring a belief over task parameters, using variational inference methods. Motivated by recent successes of contrastive learning approaches in RL, such as contrastive predictive coding (CPC), we investigate whether contrastive methods can be used for learn...
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We study a hybrid distributed model, which combines message-passing and shared-memory communication layers, and investigate the minimal number of failures that can partition such systems. We prove that this number precisely captures the resilience that can be achieved by algorithms that implement a variety of shared objects and solve common tasks, like approximate agreement. In the cluster-based model, processes are partitioned into disjoint clusters. We solve the approximate ag...
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Blockchain Networks, especially those with Smart Contracts, are well-known examples of Active Replication Systems. Active Replication Services are available thanks to a group of servers called replicas that handle client requests. Each server maintains a local copy of the global state of the service, and all servers update their local copy at synchronized incremental steps. At the i-th step, all servers receive the *same* transaction from a global ordering service, execute it and ...
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For my PhD thesis seminar, I will be presenting two of my works related to the security and reliability of distributed services in the face of Byzantine attacks. In the first work “Not a COINcidence: Sub-Quadratic Asynchronous Byzantine Agreement WHP” (DISC’20), I present a solution for binary Byzantine Agreement (BA) in asynchronous systems, using a shared coin algorithm based on a VRF and VRF-based committee sampling. My algorithms work against a delayed-adaptive adversary...
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Rephael Wenger is a professor in the computer science and engineering department of The Ohio State university where he works on geometric modeling, mesh generation, geometric algorithms and scientific visualization....
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One thing that distinguishes (theoretical) computer science from other scientific disciplines is its full-throated support of a fundamentally adversarial view of the universe. Malicious adversaries, with unbounded computational advantages, attempt to foil our algorithms at every turn and destroy their quantitative guarantees. However, there is one strange exception to this world view and it is this: the algorithm must accept its input as sacrosanct, and may never simply reject its...
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Proteins fold from a sequence of amino acids, forming secondary structures which subsequently fold into a three-dimensional structure that enables their function. The amino acid sequence is defined in the genetic sequence as codons, many of which are synonymous, i.e., they code for the same amino acid. The "one sequence, one structure" dogma, established over half a century ago, remains the commonly accepted notion, and implies that synonymous coding is inconsequential to protein...
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We determine all $m$-ary Boolean functions $f_0,\ldots,f_m$ and $n$-ary Boolean functions $g_0,\ldots,g_n$ satisfying the equation $f_0(g_1(z_{11},\ldots,z_{1m}),\ldots,g_n(z_{n1},\ldots,z_{nm})) = g_0(f_1(z_{11},\ldots,z_{n1}),\ldots,f_m(z_{1m},\ldots,z_{nm})),$ for all Boolean inputs $\{ z_{ij} : i \in [n], j \in [m] \}$. This extends characterizations by Dokow and Holzman[DH09] (who considered the case $g_0 = \cdots = g_n$) and by Chase, Filmus, Minzer, Mossel and Saurabh [CFMM...
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Recent non-volatile main memory technology (such as Intel’s Optane) gave rise to an abundance of research on building persistent data structures, whose content can be recovered after a system crash. While there has been significant progress in making durable data structures efficient, shortening the length of the recovery phase after a crash (in which data cannot be accessed) has not received much attention. In fact, programmers need to choose exclusively between durable data st...
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Despite significant advancements in operating system memory management, our understanding of the desired behavior of fundamental techniques introduced decades ago is sometimes incomplete or not well-defined. This can result in correctness issues that might cause the system to crash or be compromised, as well as missed opportunities for optimizations. In this talk, I will present two specific examples of this: (1) the inefficiencies in synchronizing the memory view across different...
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Atomic concurrent objects, whose operations take place instantaneously, are a powerful technique for designing complex concurrent programs. Since they are not always available, they are typically substituted with software implementations. A prominent condition relating these implementations to their atomic specifications is linearizability, which preserves safety properties of programs using them. However linearizability does not preserve hyper-properties, which include probabilis...
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Classical Proof-of-Work blockchains like Bitcoin implement a decentralized ledger, where anyone can participate. They aggregate transactions from system users in blocks and decide each block's position in the ledger. They require the block at each position to accrue votes until the probability of a decision change, due to chance or malice, is negligible. To allow consumer usage of such systems, low latency in the order of seconds is necessary. In classical blockchain systems laten...
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Imaging plays a key role in advancing science, from revealing the internal structure of clouds to providing the first visual evidence of a black hole. While both examples come from different imaging systems, they illustrate what can be achieved with modern computational approaches. Computational imaging combines concepts from physics, machine learning, and signal processing to reveal hidden structures at the smallest and largest of scales. In this talk, I will highlight how peelin...
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Vehicles possess an extraordinary amount of technological features that are meant to improve the safety and comfort of the driving experience. Those features have become so advanced that many of the driving aspects are now almost completely automated. Most drivers in the world now rely on the computer systems of the vehicle itself in order to perform even the most basic tasks, such as steering and parking. The CAN bus is the main network used for communication between the vario...
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The diagnosis and treatment planning of many diseases, such as cancer and auto-immune conditions, rely on histological slides. In recent years, digital pathology has become more abundant allowing high-thruput digitization of pathology images and the use of AI to analyze and interpret them. Yet, there are still inherent challenges in harnessing AI for pathology that includes coping with features in multiple size scales, the ability to achieve interpretability of the AI results, and...
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Amin Vahdat, in a talk that has gone viral, described the five epochs of distributed computing (https://www.youtube.com/watch?v=Am_itCzkaE0). It’s a great talk, but I disagree with him on one key point. He thinks we are early in the fifth Epoch. I say we entered the fifth Epoch several years ago and we are on the verge of the next Epoch … the sixth Epoch of distributed computing. In this talk I will very briefly outline the five Epochs of distributed computing and then s...
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The concept of a graph minor is fundamental in topological graph theory. First, I will describe the cornerstones of this theory from the lens of parameterized complexity. Next, I will survey more recent results concerning minor-hitting problems, focusing on three algorithmic paradigms: approximation, kernelization, and parameterized algorithms. Here, an important special case is the Vertex Planarization problem (remove as few vertices as possible to make a given graph planar) – ...
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You are invited to the CS Taub projects fair for the Winter Semester of 2023, where 30 teams of undergraduate students will present and demonstrate projects in various fields in IoT, Android, Arduino and Networks, developed as part of the final project in the software engineering and communication networks track, most of which were carried out in collaboration with various social associations and organizations, and were intended to make a contribution to...
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Machine learning (ML) is integrated into our society, it is present in the judicial, health, transportation, and financial systems. As the integration increases, the necessity of ML transparency increases. The fields of explainable and interpretable ML attempt to add transparency to ML: either by adding explanations to a given black-box ML model or by building a model which is interpretable and self-explanatory. Despite the importance of explainability and interpretability, th...
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The race for performance and the variety of specialized workloads drives the industry to build more parallel, heterogenous, and distributed computing systems. These systems introduce multiple programming challenges. This talk will overview the driving forces, world trends, challenges, and emerging solutions. Specifically, we will overview the oneAPI Initiative and its components and benefits. We will demonstrate SYCL's new programming paradigm and more. Biography: Guy Tamir is a ...
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Given i.i.d. samples from an unknown distribution over a large domain [N], approximating several basic quantities, including the distribution’s support size, its entropy, and its distance from the uniform distribution, requires (NlogN) samples [Valiant and Valiant, STOC 2011]. Suppose, however, that we can interact with a powerful but untrusted prover, who knows the entire distribution (or a good approximation of it). Can we use such a prover to approximate (or rather, to app...
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Mobileye representatives will visit CS to present the development of the software and algorithms of Mobileye's autonomous vehicle, the possibilities of employment and life in the company, on Wednesday, January 18, 2023, 12:30 in the Taub lobby....
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From minute surface vibrations to very fast-occurring events, the world is rich with phenomena humans cannot perceive. Likewise, most computer vision systems are primarily based on 'conventional' cameras, which were designed to mimic the imaging principle of the human eye, and therefore are equally blind to these ubiquitous phenomena. In this talk, I will show that we can capture these hidden phenomena by creatively building novel vision systems composed of common off-the-shelf co...
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Can preprocessing help reduce computational costs? We study this question in the context of communication complexity, focusing on a simple "simultaneous messages" setting in which computationally unbounded Alice and Bob each send a single message to a computationally bounded Carol. A big part of our work concentrates on the task of computing the inner product function modulo 2 by a polynomial-sized bounded-depth Boolean circuit. Without preprocessing this task was shown to be i...
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We extend the standard online worst-case model to accommodate past experience which is available to the online player in many practical scenarios. We do this by revealing a random sample of the adversarial input to the online player ahead of time. The online player competes with the expected optimal value on the part of the input that arrives online. Our model bridges between existing online stochastic models (e.g., items are drawn i.i.d. from a distribution) and the online wor...
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The generalized covering radius (GCR) was recently introduced as a fundamental property of linear codes, shown to characterize a trade-off between storage amount, access complexity, and latency in linear data querying protocols (such as many PIR protocols). In the general case (where the codes are not necessarily linear), the GCR is used in order to formulate a higher-order version of the famous combinatorial football-pool problem. During this talk, we shall discuss the equivalent...
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Boolean sum and ruling are two well-known construction operators for both parametric surfaces and trivariates. In many cases, the input freeform curves in R^2 or surfaces in R^3 are complex, and as a result, these construction operators might fail to build the parametric geometry so that it has positive Jacobian throughout the domain. In this work, we focus on cases in which those constructors fail to build parametric geometries with a positive Jacobian throughout while the ...
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Following the immense recent advances in distributed networks, the explosive growth of the Internet, and our increased dependency on these infrastructures, guaranteeing the uninterrupted operation of communication networks has become a major objective in network algorithms. The modern instantiations of distributed networks, such as the Bitcoin network and cloud computing, introduce new security challenges that deserve urgent attention in both theory and practice. In this talk, ...
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Introducing parallelism to applications is a complex and tedious task. As a result, the field named automatic parallelization emerged. Automatic parallelization refers to the seamless introduction of parallel schemes (such as OpenMP directives) to code. In other words, creating a tool that will mimic the human comprehension process to insert parallelization schemes. In the recent past, the main focus of this field was on creating deterministic tools such as specific functionality ...
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Private information retrieval (PIR) addresses the question of how to retrieve data items from a database or cloud without disclosing information about the identity of the data items retrieved. The area has received renewed attention in the context of PIR from coded storage. Here, the files are distributed over the servers according to a storage code instead of mere replication. Alongside with the basic principles of PIR, we will review recent capacity results and demonstrate the u...
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Abstract: We consider the budgeted matroid independent set problem. The input is a ground set, where each element has a cost and a non-negative profit, along with a matroid over the elements and a budget. The goal is to select a subset of elements which maximizes the total profit subject to the matroid and budget constraints. Several well known special cases, where we have, e.g., a uniform matroid and a budget, or no matroid constraint (i.e., the classic knapsack problem), admit a...
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You are invited to an Open Source workshop on open source and how contributing to open source helps professional development and gaining experience at any stage of your career, in a lecture by Michal Forg, front end developer at Gong company and manager of the largest open source community in Israel, Pull Request, on Tuesday, January 10, 2023 at 18:30 in Taub 337. ...
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Electronic voting systems are essential for holding virtual elections, and the need for such systems increases due to the COVID-19 pandemic and the social distancing that it mandates. One of the main challenges in e-voting systems is to secure the voting process: namely, to certify that the computed results are consistent with the cast ballots, and that the privacy of the voters is preserved. We propose secure voting protocols for elections that are governed by two central familie...
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VAYYAR representatives will visit CS to present products and developments and to offer open positions, on Wednesday, January 11, 2023, 12:30, Taub lobby....
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Neural volumetric representations have become a widely adopted model for radiance fields in 3D scenes. These representations are fully implicit or hybrid function approximators of the instantaneous volumetric radiance in a scene, which are typically learned from multi-view captures of the scene. We investigate the new task of neural volume super-resolution - rendering high-resolution views corresponding to a scene captured at low resolution. To this end, we propose a neural super-...
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Our modern life is marked by continuous interaction with huge and complex computational environments, a setting which gives rise to numerous theoretical and algorithmic challenges. Algorithms nowadays are often required to optimize objectives that may be theoretically ill-defined, on big data that is complex-structured, while maintaining computational efficiency and provable guarantees such as privacy and robustness. In this talk I will discuss some of my work developing new compu...
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We consider the online Submodular Welfare problem. In this problem we are given n bidders each equipped with a submodular utility and m items that arrive online. The goal is to assign each item, once it arrives, to a bidder or discard it, while maximizing the sum of utilities. The case of monotone utilities has attracted much attention, however much less is known once utilities are general and not necessarily monotone. When an adversary determines the items' arrival o...
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Intel will hold a recruitment day and will present employment opportunities, as well as a "Fusion 360" workshop of 3D modeling, printing and Makers experience, on Wednesday, January 4, 2023, starting at 12:30 in the Taub lobby. For the workshop please ...
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We study close connections between Indistinguishability Obfuscation (IO) and the Minimum Circuit Size Problem (MCSP), and argue that algorithms for one of MCSP or IO would empower the other one. Some of our main results are: If there exists a perfect (imperfect) IO that is computationally-secure against non-uniform polynomial-size circuits, then we obtain fixed-polynomial lower bounds against NP(MA). In addition, computationally-secure IO against non-uniform polynomial-size ...
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The field of natural language processing (NLP) has been advancing in giant strides over the past several years. The main drivers of this success are: (1) scaling the Transformer deep network architecture to unprecedented sizes and (2) “pretraining” the Transformer over massive amounts of unlabeled text. In this talk, I will describe efforts to provide principled guidance for the above main components and further thrusts in contemporary NLP, aimed to serve as timely constructiv...
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Magnetic resonance imaging (MRI) is a powerful, ionizing-radiation-free medical imaging modality. The vast physical and physiological parameters, which MRI is sensitive to, makes it possible to visualize both structure and function in the body. However the prolonged time necessary to capture the information in this large parameter space remains a major limitation of this phenomenal modality, which the field of computational MRI aims to address. By computational MRI we refer to the...
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Causal inference is fundamental to empirical research in natural and social sciences and is essential for scientific discoveries. Two key challenges for conducting causal inference are (i) acquiring all attributes required for the analysis, and (ii) identifying which attributes should be included in the analysis. Failing to include all necessary attributes may lead to false discoveries and erroneous conclusions. However, in real-world settings, analysts may only have access to par...
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Yahoo Research will visit CS for a special meeting with graduate students on Tuesday, January 3, 2023 starting at 10:30 at the Grads Club, 2nd floor (at the end of the corridor), Taub Computer Science Building: Program: 10:30 - Gathering 11:00 - Intro - Yahoo Israel Research Center 11:15 - Lecture 1: Leveraging User Email Actions to Improve Ad-Close Prediction - by Yar...
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You are invited to Microsoft Recruitment day, to a question and answer session with the team about the company's recruitment process, and to a lecture by Noa Berman, a software developer at Microsoft Security, on: Ransomware attacks and how we defend against them at Microsoft Defender for Endpoint, on Monday, January 2, 17:30, at Taub 9. Please pre-register....
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