The Taub Faculty of Computer Science Events and Talks

In the metric compression problem, we are given n points in a metric space, and the goal is to construct a compact representation (sketch)of the points, such that the distance between every pair can be approximate lyre covered from the sketch, up to a small ...
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We present the first general and practical solution of the fluent API problem – an algorithm, that given a deterministic language (equivalently, LR(k), k≥0 language) encodes it in an unbounded parametric polymorphism type system employing only a polynomial number of types. The theoretical result is ...
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Leveraging Programmable Switches for In-network Computing The network line rate is constantly on the rise to support the exploding amounts of data. This means that we have less time to process individual packets, despite a growing demand for better network telemetry. Moreover, CPU speeds are ...
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The security and architecture communities will remember 2018 as the year of side channels. Starting from Spectre and Meltdown, time and again we have seen how basic performance-improving features can be exploited to violate fundamental hardware security guarantees. In this talk, I will survey two ...
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In recent years, new forms of communication between people and devices have revolutionized our daily lives. The Internet has become the leading platform for human interaction (e.g., social networks), commerce, information, and also control of physical devices (e.g., Internet of Things). This new connectivity creates ...
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In 2010, Patrascu proposed the Multiphase problem, as a candidate for proving polynomial lower bounds on the operational time of dynamic data structures. Patrascu conjectured that any data structure for the Multiphase problem must make n cell-probes in either the update or query phase, and ...
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Learning systems have become ever more pervasive in our lives. By controlling the flow of information, they play an increasingly significant role in shaping decisions made by us, about us, and for us. But systems are still developed under paradigms in which human actors are ...
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Approximating ranks, quantiles, and distributions over streaming data is a central task in data analysis and monitoring. Given a stream of n items from a data universe U (equipped with a total order), the task is to compute a sketch (data structure) of size poly(log(n), ...
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Existing proofs that deduce P=BPP from circuit lower bounds convert randomized algorithms to deterministic ones with a large polynomial slowdown in running time. In this talk, I will show that if we assume exponential lower bounds against nondeterministic circuits, we can convert any randomized algorithm ...
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In recent years, new forms of communication between people and devices have revolutionized our daily lives. The Internet has become the leading platform for human interaction (e.g., social networks), commerce, information, and also control of physical devices (e.g., Internet of Things). This new connectivity creates ...
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There is a recent surge of interest in performing computations on encrypted data. Techniques such as secure multi-party computations and fully-homomorphic encryption enable rich privacy-preserving applications. On the other hand, building such applications is hard due to the cryptographic expertise required to build them correctly, ...
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Although distributed computing can significantly reduce the training time of deep neural networks, scaling the training process while maintaining high efficiency and final accuracy is challenging. Cloud computing, which is becoming increasingly popular as a platform for distributed training of deep neural networks, is prone ...
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Efficient learning requires prior knowledge (inductivebias). The algorithm designer can manually insert a prior based on hisintuition, but ideally, we would like to automatically infer the mostbeneficial prior. In meta-learning an agent extracts a ‘learned prior’ fromseveral observed learning tasks, which in turn, can be ...
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Establishing a low network latency connection to stock exchanges has been the desire of trader for years. A well-known example is the extremely expensive construction of an ultra-low latency fiber optic cable between New York and Chicago just for reducing three millisecond in the round ...
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Data is one of the most important assets of the information age, and its societal impact is undisputed. Yet, rigorous methods of assessing the quality of data are lacking. In this talk, we propose a formal definition for the quality of a given static dataset. ...
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I will speak about an unexpected correspondence between a beautiful theory, due to Lovasz, about homomorphisms and graph limits and a popular heuristic for the graph isomorphism problem known as the Weisfeiler-Leman algorithm. I will also relate this to graph kernels in machine learning. Indeed, ...
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Effective data analysis often depends on data that is known to different sources, including private data whose owners cannot disclose. The task at hand is to perform effective analysis of the data while preserving its privacy. This talk will describe efficient cryptographic protocols, some of ...
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In the 'frequent items' problem one sees a sequence of items in a stream (e.g. a stream of words coming into a search query engine like Google) and wants to report a small list of items containing all frequent items. In the 'change detection' problem ...
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The PPSZ algorithm, due to Paturi, Pudlak, Saks and Zane, is currently the fastest known algorithm for the k-SAT problem, for every k>3. For 3-SAT, a tiny improvement over PPSZ was obtained by Hertli. We introduce a biased version of the PPSZ algorithm using which ...
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In the Bounded Degree Matroid Basis Problem, we are given a matroid and a hypergraph on the same ground set, together with costs for the elements of that set as well as lower and upper bounds f(e) and g(e) for each hyperedge e. The objective ...
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We present a method for determining which facial parts (mouth, nose, etc.) best characterize an individual, given a set of that individual's portraits. We introduce a novel distinctiveness analysis of a set of portraits, which leverages the deep features extracted by a pre‐trained face recognition ...
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Consider an instance of Euclidean k-means or k-medians clustering. We show that the cost of the optimal solution is preserved up to a factor of (1+ε) under a projection onto a random - dimensional subspace. Further, the cost of every clustering is preserved within (1+ε). ...
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Interactive oracle proofs are a hybrid between interactive proofsand probabilistically-checkable proofs, where the prover is allowed to interactwith a verifier by sending relatively long messages to the verifier, who inturn is only allowed to query a few of the bits that were sent. In this ...
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The Network Time Protocol (NTP) synchronizes time across computer systems over the Internet. Unfortunately, NTP is highly vulnerable to “time shifting attacks”, in which the attacker’s goal is to shift forward/backward the local time at an NTP client. NTP’s security vulnerabilities have severe implications for ...
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Photos and videos are now a main mode of communication, used to tell stories, share experiences and convey ideas. However, common media editing tools are often either too complex to master, or oversimplified and limited. In this talk I will present my strategy towards the ...
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SINR (aka physical model) is a model of wireless communication that has been studied from algorithmic perspective in the last decade, and is considered as a more realistic alternative to the traditional graph-based models. I will introduce the model and discuss some basic scheduling problems. ...
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SpaceIL made history when Beresheet, the first privately funded spacecraft, have reached the Moon with a minute budget of 100M$. After eight years of planning, Beresheet's journey started on February 22nd, 2019, when SpaceIL's lunar lander has been launched to space on top of a ...
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This paper defines the notion of class discrepancy for families of functions. It shows that low discrepancy classes admit small offline and streaming coresets. We provide general techniques for bounding the class discrepancy of machine learning problems. As corollaries of the general technique we bound ...
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Traditional query optimizer is crucially dependent on cardinality estimation, which enables choosing among different plan alternatives by using the cardinality estimation of intermediate results within query execution plans. Therefore, the query optimizer must use reasonably good estimates. However, estimates produced by all widely-used database cardinality ...
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The overlapping correlation clustering problem has multiple real-world applications in diverse areas such as: social networks (community detection), biology (protein analysis) and information retrieval (categorising documents). Correlation clustering is a problem of assigning data points into distinct groups (clusters) based on similarity. When assigning two ...
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Lifting theorems are theorems that relate the query complexity of a function $f : \{0, 1\}^{n} \rightarrow \{0, 1\}$  to the communication complexity of the composed function fgn, for some “gadget” $g  : \{0, 1\}^{b} \times \{0, 1\}^{b} \rightarrow \{0, 1\}$. Such theorems allow transferring ...
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When this logician moved to theoretical computer science, this did not seem such a big deal to him. The transition was seamless. The transition to software engineering was radical. Microsoft research invited me to come, start a group and use my ideas to build tools. ...
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Reparameterization of variational auto-encoders with continuous random variables is an effective method for reducing the variance of their gradient estimates. Our work optimizes the discrete VAE objective directly, using its Gumbel-Max reparameterization. This optimization technique propagates gradients through the reparameterized argmax, and replaces MCMC sampling ...
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Learning to generate music is an ongoing AI challenge. A more difficult challenge is the generation of musical pieces that match human-specific preferences. In this work we focus on personalized, symbol-based, monophonic generation of harmony-constrained jazz improvisations. To tackle this objective, we introduce a pipeline ...
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Suppose we receive a stream of data, sampling each arriving data element with some predetermined probability. It is well known that if the elements in the stream are chosen in advance, then a constant number of random samples suffice to make the sampled subset “represent” ...
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Artificial neural networks are nowadays routinely trained to solve challenging learning tasks, but our theoretical understanding of this phenomenon remains quite limited. One increasingly popular approach, which is aligned with practice, is to study how making the network sufficiently large (a.k.a. ''over-parameterized'') makes the associated ...
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In many common datasets, neural networks can achieve zero training loss yet generalize well to unseen data. Recent works suggest that this because standard training algorithms (e.g., GD or SGD) have an implicit regularization which is biased towards specific solutions, which tend to have good ...
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How does the brain beget the mind? How do molecules, cells and synapses effect reasoning, intelligence, language, science? Despite dazzling progress in experimental neuroscience we do not seem to be making progress in the overarching question -- the gap is huge and a completely new ...
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This work is dedicated to eliminating the overhead required for guaranteeing the storage order in the modern IO stack. The existing block device adopts a prohibitively expensive approach in ensuring the storage order among write requests: interleaving the write requests with Transfer-and-Flush. Exploiting the cache ...
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The talk is about anti-concentration of the inner product of two independent random vectors in Euclidean space. We shall discuss a proof, and some applications
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Technion CS celebrates jubilee and invites you to CS City - a festival of science and technology for the whole family which will be held on Tuesday, October 29, 2019 starting at 4:30 pm at the CS Taub Building, Technion. Participation is free, but pre-registration ...
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Election databases are the main elements of a recently introduced framework that aims to create bridges between the computational social choice and the data management communities. An election database consists of incomplete information about the preferences of voters, in the form of partial orders, alongside ...
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Managing data inconsistency has been one of the major challenges in the research and practice of database management. Database inconsistency arises for different reasons and in different applications. Nowadays, many applications obtain information from imprecise sources (e.g., social encyclopedias, social networks, and sensors attached to ...
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A tree code is a combinatorial object introduced by Schulman in the early 90s as a key ingredient in interactive coding. Schulman proved the existence of tree codes with constant alphabet size, but the problem of explicitly constructing a tree code remained elusive. We present ...
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Inverse problems in imaging are extensively studied, with a variety of strategies, tools, and theory that have been accumulated over the years. Recently, this field has been immensely influenced by the emergence of deep-learning techniques. One such contribution, which is the focus of this paper, ...
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Large training datasets are required to achieve competitive performance in most natural language tasks. The acquisition process for these datasets is labor intensive, expensive, and time consuming. This process is also prone to human errors. In this work, we show that cross-cultural differences can be ...
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Product descriptions play an important role in the e-commerce ecosystem, conveying information to buyers about merchandise they may purchase. Yet, on leading e-commerce websites, with high volumes of new items offered for sale every day, product descriptions are often lacking or missing altogether, and when ...
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Maintaining an accurate trained model on an infinite data stream is challenging due to concept drifts that render a learned model inaccurate. Updating the model periodically can be expensive, and so traditional approaches for computationally limited devices involve a variation of online or incremental learning, ...
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On Wednesday, September 11, TCE center will host this year the 9th annual Henry Taub International Conference on Autonomous Systems and will focus on the advent of autonomous systems including self-driving cars, automatic delivery drones, and service robots considered by many a major revolution of ...
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Non-volatile memory is expected to co-exist or replace DRAM in upcoming architectures. Durable concurrent data structures for non-volatile memories are essential building blocks for constructing adequate software for use with these architectures. In this paper, we propose a new approach for durable concurrent sets and ...
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We construct a new interactive polynomial commitment scheme using groups of unknown order. The interactive evaluation argument is public-coin and has logarithmic communication in the degree of the polynomial. The scheme does not require a trusted setup if instantiated with class groups. We apply this ...
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In the field of population genetics, it is known that collected observations are not independent, as they all share a common ancestor. Current state-of-the-art association tests use Monte Carlo simulations to account for these dependency structures. However, these simulations are not scalable and are cumbersome ...
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The purpose of this research is to explore an innovative approach to the declarative and imperative paradigms of programming languages. To demonstrate this approach, we have developed a prototype domain-specific language inspired by the scripts of theatrical plays, hence dubbed Tʜᴀᴘʟ. Tʜᴀᴘʟ's intended use is ...
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Massively parallel, throughput-oriented processors are becoming increasingly common. Maximizing the benefit of these processors requires algorithms to be implemented differently than the sequential algorithms that most software developers are familiar with. This change is often very time-consuming and is not guaranteed to give an increase ...
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Real-world networks are dynamic in nature -- nodes may join or leave the network at any time, and communication links may appear or disappear constantly. In this dynamic setting, we study the problem of triangle detection, where the nodes of a network need to determine, ...
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Concurrent data structures provide fundamental building blocks for concurrent programming. Standard concurrent data structures may be extended by allowing a sequence of operations to be submitted as a batch for later execution. A sequence of such operations can then be executed more efficiently than the ...
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Numerical geometry comprises of principled computational methods that utilize theoretical insights from geometry along with the engineering concepts from numerical methods, for tackling various problems in geometric data analysis. In contrast, computational methods from recent advances in deep learning exhibit a black box nature where ...
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Jigsaw puzzle solving is an intriguing problem, having a wide variety of applications in archaeology, biology, document restoration and others. This paper focuses on a specific variant of the problem - solving puzzles with eroded boundaries. Such erosion makes the problem extremely difficult, since most ...
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Suboptimal resource utilization among public and private cloud providers prevents them from maximizing their economic potential. Long-term allocated resources are often idle when they might have been subleased for a short period. Alternatively, arbitrary resource overcommitment may lead to unpredictable client performance. We propose a ...
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The information in the weights of deep networks plays a key role in understanding their behavior. When used as a regularizer during training (either explicitly or implicitly) it induces generalization through the PAC-Bayes bound. Rather than being computed and minimized explicitly, it can be directly ...
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Recent years have seen great progress in automated synthesis techniques that can automatically generate code based on some intent expressed by the user, but communicating this intent remains a major challenge. When the expressed intent is coarse-grained (for example, restriction on the expected type of ...
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The omnipresence of increasingly large deep networks derives primarily from their empirical successes. Indeed, empirical evidence places a strong emphasis on operating at scale, more parameters and layers, in order to help both optimization and generalization. This counter-intuitive trend has eluded theoretical analysis. In this ...
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Different methods where presented through the years to find good solutions for the Matrix Completion Problem. This problem appears in many tasks in life where a sparse signal, which lies on a grid of two non- Euclidean domains (Graphs or manifolds), should be predicted or ...
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This talk will present our approach for enumerating the results of queries in monadic second-order (MSO) on trees. Our goal is to first preprocess the input tree in linear time, and then enumerate the answers with delay linear in the size of each answer, i.e., ...
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Applications' memory consumption is growing rapidly, which increases their dependence on the memory system. Since each virtual-to-physical memory translation in modern systems requires cache lookups or multiple memory accesses, the run time overhead of virtual memory translation is on the rise. Meanwhile, the increasing prevalence ...
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Whereas deterministic protocols are typically guaranteed to obtain particular goals of interest, probabilistic protocols typically provide only probabilistic guarantees. In this talk we initiate an investigation of the interdependence between actions and subjective beliefs of agents in a probabilistic setting. In particular, we study what ...
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Rank-metric codes (RMCs) over finite fields were introduced some 40 years ago by Delsarte, Gabidulin and Roth. Interest in RMCs was revived in recent years due to the application of such codes to network coding. In 1991, another simple construction of a class of RMCs ...
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Rigid registration is the problem of finding the optimal rigid motion and correspondence between two shapes, so that they are as similar as possible in terms of an appropriate energy. We will describe several popular algorithms for this problem: PCA alignment and ICP, which are ...
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In this talk, we will look at decoding Reed-Muller codes beyond their minimum distance when the errors are random (i.e., in the binary symmetric channel). A beautiful result of Saptharishi, Shpilka and Volk showed that for binary Reed-Muller codes of length n and degree n ...
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Shape correspondence is a fundamental task in shape analysis. Given two shapes, the goal is to compute a semantic correspondence between points on them. Shape correspondence is required when two shapes are analyzed jointly, which is common in many applications such as texture and deformation ...
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Modern cloud architectures rely on each server running a software-defined networking stack to implement policy and virtualization. However, these networking stacks are becoming increasingly complex as features are added and as network speeds increase. Running these stacks on CPU cores takes away processing power from ...
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It is widely known that in the well-studied \LOCAL model of distributed computing, introduced by Linial [FOCS '87], many of the classic distributed graph problems (including maximal independent set (MIS) and MaxDegree+1-vertex coloring), have very efficient (and simple) randomized but exponentially slower deterministic algorithms. Understanding ...
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A fundamental question in learning to classify 3D shapes is how to treat the data in a way that would allow us to construct efficient and accurate geometric processing and analysis procedures. Here, we restrict ourselves to networks that operate on point clouds. There were ...
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CS Labs: Systems and Software Development Laboratory (SSDL), Cyber and Computer Security Laboratory (CYBER), The Laboratory for Computer Communication and Networking (LCCN) invite you to visit the Spring Project Fair in IoT, Software, Android Apps, AI, Cyber, Computer Security, and Networks, including demos and presentations ...
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The 9th CS Research Day for graduate studies will be held on Monday, June 24, 2019 between 15:00-17:00, 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 ...
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Datacenter congestion control remains to be a hard problem. The root of the problem is that the ability of end-hosts to react to congestion is fundamentally limited by the timeliness and precision of congestion signals from the network. Unfortunately, despite decades of research, the community ...
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In this talk, a new family of codes called clustering-correcting codes is presented. This family of codes is motivated by the special structure of data that is stored in DNA-based storage systems. The data stored in these systems has the form of unordered sequences, also ...
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I'll discuss our novel discrete scheme for simulating viscous thin films in 2D at real-time frame rates. Our scheme is based on a new formulation of the gradient flow approach, that leads to a discretization based on local stencils that are easily computable on the ...
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Abstract: One of the main tasks in three-dimensional shape analysis is to retrieve similarities between two or more non-rigid objects in terms of point-to-point correspondences. For the descriptor based approach, it is useful to construct a simplified shape representation called feature descriptor. A successful descriptor ...
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We develop a new approach for distributed distance computation in planar graphs that is based on a variant of the metric compression problem recently introduced by Abboud et al. [SODA'18]. In our variant of the Planar Graph Metric Compression Problem, one is given an $n$-vertex ...
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Approximating high-dimensional functionals with low-dimensional models is a central issue of machine learning, image processing, physics and mathematics. Deep convolutional networks are able to approximate such functionals over a wide range of applications. This talk shows that these computational architectures take advantage of scale separation, ...
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The new and highly effective techniques frequently associated with Artificial Intelligence, including machine learning, pattern recognition, natural language processing, robotics, image analysis, and nonlinear optimization will have profound effects on the ways research is done and the sorts of projects that are feasible. There is ...
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In this talk, we consider the problem of communicating over a discrete memoryless two-way channel using non-adaptive schemes, under a zero probability of error criterion. We derive inner and outer bounds on the zero-error capacity region, based on random coding, linear programming, and linear codes.
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I will present the 'virtual democracy' framework for the design of ethical AI. In a nutshell, the framework consists of three steps: first, collect preferences from voters on example dilemmas; second, learn models of their preferences, which generalize to any (previously unseen) dilemma; and third, ...
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Many natural language understanding (NLU) tasks consist of identifying the relationship between two objects, such as a paragraph and a question (reading comprehension), an image and a question (visual question answering), or a premise and a hypothesis (natural language inference). These tasks supposedly require a ...
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In recent years, cloud providers have been moving towards offering their clients separate cloud resources for short periods of time instead of offering bundles of resources for longer periods. In parallel, the providers are moving towards using economic mechanisms, such as auctions, to allocate these ...
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Recent advances in manufacturing techniques have greatly expanded the types and complexity of shapes that can be produced. At the same time, advances in AI (esp. machine learning) and physics driven algorithms (e.g., topology optimization) have enabled novel methods and workflows for design engineering. A ...
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You are invited to a workshop on Image Processing, Computer Vision, Computer Graphics and Virtual Reality which will be held on Thursday, June 13, 2019, in Room 337, 09:00-12:20, CS Taub Building. More details and full program in the attached poster Please pre-register. You are ...
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This work provides an additional step in the theoretical understanding of neural networks. We consider neural networks with one hidden layer and show that when learning symmetric functions, one can choose initial conditions so that standard SGD training efficiently produces generalization guarantees. We empirically verify ...
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In this talk, I will describe several research projects developed in the Berkeley Architecture Research group which utilize FPGA-accelerated simulation and open-source hardware, demonstrating the possibilities and accessibility of full-system computer architecture research using these tools and methodologies. FireSim is an easy-to-use, open-source, FPGA-accelerated cycle-accurate ...
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The last decade saw a tremendous empirical success of machine learning algorithms, which often can not be explained theoretically using a worst-case analysis. Therefore, it is a great challenge to identify reasonable assumptions under which the theory is aligned with the practice. In this talk ...
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Reactive synthesis is an automated procedure to obtain a correct-by-construction reactive system from a given declarative, temporal specification. Examples of these systems include the software controllers of robotic systems. Despite recent advancements on the theory and algorithms of reactive synthesis, e.g., efficient synthesis for the ...
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We present a Monte Carlo rendering framework for the physically-accurate simulation of speckle patterns arising from volumetric scattering of coherent waves. These noise-like patterns are characterized by strong statistical properties, such as the so-called memory effect. These properties are at the core of imaging techniques ...
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3D objects, modeled using Computer Aided Geometric Design (CAGD) tools, are traditionally represented using a boundary representation (B-rep), and typically use spline functions to parameterize these boundary surfaces. However, recent development in physical analysis, in isogeometric analysis (IGA) in specific, necessitates a volumetric parametrization of ...
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Blockchains are distributed secure ledgers to which transactions are issued continuously and each block of transactions is tightly coupled to its predecessors. Permissioned blockchains place special emphasis on transactions throughput. In this paper we present TOY, which leverages the iterative nature of blockchains in order ...
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Containers (or Operating System based Virtualization) are an old technology; however, the current excitement (and consequent investment) around containers provides interesting avenues for research on updating the way we build and manage container technology. The most active area of research today, thanks to concerns raised ...
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Arguably the most common network communication problem is multiple-unicasts: Distinct packets at different nodes in a network need to be delivered to a destination specific to each packet, as fast as possible. The famous multiple-unicast conjecture posits that, for this natural problem, there is no ...
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In the last six years, Bitcoin has obtained a good deal of attention, reaching in May 2019 a market capitalization of more than one hundred and fifty billion (US) dollars and a daily trading volume of hundreds of millions of dollars. Although Bitcoin is considered ...
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Visual acuity (VA) tests are widely used in ophthalmology to measure vision quality, but even modern tests still rely on an algorithm created in 1976 \cite{Bailey1976}. This algorithm is basically the original VA test algorithm from 1873 \cite{Snellen1873}, with minor modifications. The tests measure VA ...
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Computation integrity (CI) protocols allow a strong prover to convince a skeptic verifier it has knowledge of an input satisfying a program. Although theoretical CI constructions are well known for almost 30 years, industrial adaption has only recently started. In this seminar we will go ...
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Deep neural networks (DNNs) have recently shown great success in many machine learning domains and problems. However, applying these models for mission critical tasks still has many safety issues due to prediction uncertainty and prediction errors. This talk covers several related results concerning uncertainty estimation, ...
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The sequence reconstruction problem corresponds to a model in which a sequence from some code is transmitted over several noisy channels. The channels are almost independent as it is only required that their outputs are different. The main problem under this paradigm is to determine ...
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Manufacturing techniques such as hot-wire cutting, wire-EDM, wire-saw cutting, and flank CNC machining all belong to a class of processes called line-cutting where the cutting tool moves tangentially along the reference geometry. From a geometric point of view, line-cutting brings a unique set of challenges ...
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I will discuss our recent shortest paths algorithms in the distributed congested clique model. Our first contribution is a (2+epsilon)-approximation algorithm for all-pairs shortest paths (APSP) requiring only polylogarithmic number of rounds. This is the first sub-polynomial constant approximation for APSP in this model. We ...
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Graph processing is typically considered to be a memory-bound rather than compute-bound problem. One common line of thought is that more available memory bandwidth corresponds to better graph processing performance. However, in this talk, I will show that this is not necessarily the case. I ...
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Artificial neural networks have recently revolutionized the field of machine learning, demonstrating striking empirical success on tasks such as image understanding, speech recognition and natural language processing. However, we still do not have sufficient theoretical understanding of how such models can be successfully learned. Two ...
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A prominent property of natural images is that groups of similar patches within them tend to lie on low-dimensional subspaces. This property has been previously used for image denoising, with particularly notable success via weighted nuclear norm minimization (WNNM). In this work, we extend the ...
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The aim of photometric stereo is to estimate shape and appearance of a three-dimensional object from multiple input images taken from the same point of view but under different lighting conditions. The most common techniques are conceptually close to the classic photometric stereo problem, meaning ...
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A robust positioning pattern is a large array that allows a mobile device to locate its position by reading a possibly corrupted small window around it. In this talk, we focus on the 1-dimensional case, i.e., robust positioning sequences (RPS). We present constructions of RPSs ...
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In the classical derandomization problem, we are given a description of a Boolean circuit, and want to deterministically approximate its acceptance probability, up to a small constant error (say, 1/6). This problem is intimately related to circuit lower bounds, and extensive efforts have been devoted ...
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Instead of using full cycle-accurate simulations, recent virtual memory studies frequently utilize linear models to predict application runtimes from TLB misses. The benefit of the latter methodology is that it is easier and much faster than the former, but its correctness has never been validated. ...
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Dynamically-typed programming languages such as Python, Ruby and JavaScript are widely used, and much effort is spent on making them efficient. One substantial research effort in this direction is the enabling of parallel code execution. As a first step towards efficiently synchronizing such languages, we ...
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Hyperspectral imaging allows measuring the spectrum of each pixel in the image of a scene. This modality has diverse applications, ranging from agriculture and geoscience, to biomedical imaging and surveillance. However, most existing methods require dedicated cameras, which make use of extra optical elements (prisms, ...
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In this talk, we consider locally repairable codes which are optimal with respect to the Singleton-type bound presented by Prakash \emph{et al.} New upper bounds on the length of such optimal codes are derived. The new bounds both improve and generalize previously known bounds. We ...
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Floater–Hormann interpolants constitute a family of barycentric rational interpolants based on the blend of local polynomial interpolants of degree d that have recently proved to be a viable alternative to more classical interpolation methods, such as polynomials and splines, especially in the equispaced setting. In ...
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Shape correspondence is a fundamental task in shape analysis, with a variety of applications in computer graphics and computer vision. Example applications include statistical shape interpolation, texture, segmentation and deformation transfer, and application of deep learning to 3D shapes. Formulating the desired geometric properties of ...
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Shape correspondence is a fundamental task in shape analysis, with a variety of applications in computer graphics and computer vision. Example applications include statistical shape interpolation, texture, segmentation and deformation transfer, and application of deep learning to 3D shapes. Formulating the desired geometric properties of ...
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We show that Folded Reed-Solomon codes achieve list decoding capacity with constant list sizes, independent of the block length. Prior work yielded list sizes that are polynomial in the block length, and relied on elaborate subspace evasive machinery to reduce the list sizes to constant. ...
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With their introduction in 2009, cryptocurrencies brought the promise of a global decentralized payment system. However, protocol limitations prevent them from managing the required throughput. Previous work overcame protocol limitations and used low-degree sharding to allow for parallelization. All these systems rely on efficient validation ...
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We will consider the SITA server farm scheduling policies which were introduced and studied by Harchol-Balter and her collaborators. In particular we will discuss a recent INFOCOM17 paper of Doncel, Aalto and Ayesta and relate one of the tables there to the work of Riemann ...
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Faculty and Graduate students are invited to a workshop on “Machine Learning on the AWS Cloud” on Monday, May 13, 2019, 15:00-18:30, in room 337, CS Taub Building. More details and program in the attached poster and document. Please RSVP by email to: awstomer at ...
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Artificial illumination plays a vital role in human civilization. In computer vision, artificial light is extensively used to recover 3D shape, reflectance, and further scene information. However, in most computer vision applications using artificial light, some additional structure is added to the illumination to facilitate ...
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Mobile sensing is an emerging research area with many applications, including environmental monitoring and medical imaging. For example, tomography, which is used extensively in medical imaging, can be re-formulated by means of sampling along trajectories in the sinogram domain. We propose a model that accounts ...
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Consider the following hat guessing game: nn players are placed on nn vertices of a graph, each wearing a hat whose color is arbitrarily chosen from a set of qq possible colors. Each player can see the hat colors of his neighbors, but not his ...
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We are happy to invite your to the fourth of series of meetings on career and job seeking which will be held at CS, on Wednesday, May 1, at 12:30, in Taub Classroom 7, CS Taub Building. Mr. David Gross, Program Engineer in Facebook Israel ...
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We study the communication complexity of welfare maximization in combinatorial auctions with m items and two subadditive bidders. A 12-approximation can be guaranteed by a trivial randomized protocol with zero communication, or a trivial deterministic protocol with O(1) communication. We show that outperforming these trivial ...
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In recent years, cryptocurrencies, and blockchain as their underlying technology have emerged. They act as a decentralized ledger, i.e., an append-only log, where payments are recorded. One of the key limitations of almost all blockchains is the overall throughput, e.g., in Bitcoin, the first cryptocurrency, ...
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Automated agents that interact proficiently with people can be useful in supporting, training or replacing people in complex tasks. The inclusion of people presents novel problems for the design of automated agents’ strategies. People do not necessarily adhere to the optimal, monolithic strategies that can ...
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A deep learning approach to numerically approximate the solution to the Eikonal equation is introduced. The proposed method is built on the fast marching scheme which comprises of two components: a local numerical solver and an update scheme. We replace the formulaic local numerical solver ...
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We propose a controllable geometric flow that decomposes the interior volume of a triangular mesh into a collection of encapsulating layers, which we denote by a generalized foliation. For star-like genus zero surfaces we show that our formulation leads to a foliation of the volume ...
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We propose a controllable geometric flow that decomposes the interior volume of a triangular mesh into a collection of encapsulating layers, which we denote by a generalized foliation. For star-like genus zero surfaces we show that our formulation leads to a foliation of the volume ...
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Many intractable computational problems on graphs admit tractable algorithms when applied to trees or forests. In such cases, a tree decomposition of the input graph often facilitates an effective solution. Therefore, tree decompositions are critical for graph problems in the fields of databases, game theory, ...
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The 2019 open day invites outstanding undergraduates from all universities to come to the Technion and learn about the Computer Science and Department, to meet faculty and graduate students and to hear a fascinating talk by Dr. Tal Cohen, Director of Program Development at Google: "Do ...
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Modern machine learning models exhibit super-human accuracy on tasks from image classification to natural-language processing, but accuracy does not tell the entire story of what these models have learned. Does a model memorize and leak its training data? Does it contain hidden backdoor functionality? In ...
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Question Answering (QA) is one of the core tasks in natural language understanding. This task requires the ability to process and understand natural language questions and documents, as well as to extract the answers to these questions. There are several settings for the QA task, ...
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This talk presents some of the geometrical aspects involved in treating irregular heart beat rhythm (Arrythmia) using Carto 3 System. Carto 3 is a product of Biosense-Webster, a global leader in the science of diagnosing and treating heart rhythm disorders. CARTO 3 System enables accurate ...
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We prove a new connection between gentle measurement (where one wants to measure n quantum states, in a way that damages the states only by a little) and differential privacy (where one wants to query a database about n users, in a way that reveals ...
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The talk will survey new developments that use cryptographic tools in order to use a quantum computer even if it is operated by an untrusted party. Applications include: proofs of quantumness, certifiable randomness, privately outsourcing quantum computation (via quantum fully homomorphic encryption) and delegating quantum ...
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Information Extraction (IE) is the task of extracting structured information from textual data. We explore a programming paradigm that is supported by several IE systems where relations extracted by atomic extractors undergo a relational manipulation. In our efforts toward achieving a better understanding of IE ...
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Partial differential equations (PDEs) are indispensable for modeling many physical phenomena and also commonly used for solving image processing tasks. In the latter area, PDE-based approaches interpret image data as discretizations of multivariate functions and the output of image processing algorithms as solutions to certain ...
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Machine learning algorithms have difficulties to generalize over a small set of examples. Humans can perform such a task by exploiting vast amount of background knowledge they possess. One method for enhancing learning algorithms with external knowledge is through feature generation. We introduce a new ...
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e-lections 2019 event, organized by Prof. Eli Biham, Orr Dunkelman, Yossi Oren and the Technion Hiroshi Fujiwara Cyber Security Research Center, will be held on Sunday, April 7, 2019 at the Technion, The event will present lectures related to electronic elections and to the effect ...
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There are two well studied security notions for public key encryption schemes: security against passive adversaries and security against active adversaries. In this talk, we will discuss a new generic transformation that can upgrade the security of an encryption scheme from passive security to active ...
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Model checking is an automatic verification method that accepts a system model and a specification, and checks whether the model satisfies the specification. CTL is a branching temporal logic suitable for specifying behaviors of both software and hardware systems. In this work, we present a ...
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In this talk I will tell you how analyzing economic markets where agents have cognitive biases has led to better understanding of the communication complexity of local search procedures. We begin the talk with studying combinatorial auctions with bidders that exhibit endowment effect. In most ...
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We consider the Graph Balancing problem, where we are given an undirected multigraph with edge weights and orientation costs. The goal is to find an orientation of the edges that minimizes the worst weighted incoming degree of a vertex (also known as makespan) while minimizing ...
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The hexahedral meshing problem is the volumetric analog of the quad meshing problem, with analogous applications in finite element modeling. One might expect that frame field–based methods, which have proven effective in quad meshing, would extend naturally to the volumetric case. Unfortunately, several problems arise ...
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We study the Excluded Grid Theorem, a fundamental structural result in graph theory, that was proved by Robertson and Seymour in their seminal work on graph minors. The theorem states that there is a function f, such that for every integer g > 0, every ...
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Unravelling underlying complex structures from limited resolution measurements is a known problem arising in many scientific disciplines. We study a stochastic dynamical model with a multiplicative noise. It consists of a stochastic differential equation living on a graph, similar to approaches used in population dynamics ...
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Blockchain protocols are notoriously bad at scaling. Most protocols do work reasonably well when used in a small scale. Yet, as the network size grows, resources are added and overall computing power increases, most protocols simply do not scale. This is largely due to the ...
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Fictitious domain methods are an elegant way to circumvent a tedious discretization process, mostly meshing. The core idea is to embedded the geometrically complex model into a fictitious domain, which has zero stiffness assigned. The complexity of the model is then recovered on the integration ...
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We consider fault-tolerant boolean formulas in which the output of a faulty gate is short-circuited to one of the gate’s inputs. A recent result by Kalai et al. [FOCS 2012] converts any boolean formula into a resilient formula of polynomial size that works correctly if ...
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You are invited to the final stage of the 2019 Best Project Contest. The finalist teams will present and talk about their projects. The event will take place on Wednesday, March 20, 2019, between 12:00-14:30, at the lobby of CS Taub Building. You are all ...
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We present a novel method for computing correspondences between subdivision surfaces, represented as functional maps. We leverage two main advantages of the hierarchical structure: (1) the spectral basis functions, which are multi-resolution by construction, can be succinctly represented on a subdivision surface, and (2) the ...
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Puzzle solving is a difficult problem in its own right, even when the pieces are all square and build up a natural image. But what if these ideal conditions do not hold? One such application domain is archaeology, where restoring an artifact from its fragments ...
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Today we are literally surrounded by software. Almost all products and services we use on a daily basis involve some piece of software. The abundance of software has made our lives easier. Unfortunately it also made us susceptible than ever to software vulnerabilities and exploitation. ...
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Billions of dollars a year are spent to develop a new drug. The first step in the drug development process is drug discovery, where in potential molecules are studied before leads are selected and moved to clinical trials. Extensive research is performed to identify studies ...
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Neural Architecture Search (NAS) aims to facilitate the design of deep networks for a given task. This is part of a larger trend – automated machine learning (AutoML) – that promises to solve or at least alleviate the scarcity of ML experts needed to design ...
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In this lecture we will introduce a few quantum complexity classes (BQP, QMA, QIP, and QPIP), the Deutsch-Jozsa algorithm, and Simon's algorithm; we will finally (very briefly) discuss Shor's algorithm for factoring large numbers.
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We have witnessed worldwide network outages after large-scale natural disasters, such as earthquakes, hurricane, and terrorist attacks. In the talk, I will discuss how to extend the widely implemented single link failure models for regional failures. I will mainly focus on the related theoretical problems ...
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CYBERDAY 2019 event, organized by Prof. Eli Biham, Prof. Sara Bitan, and the Technion Hiroshi Fujiwara Cyber Security Research Center, will be held on Tuesday, March 12, 2019 at the Technion, Keynote speakers: Prof. Bart Preneel (KU Leuven, Belgium) Prof. Adi Shamir (The Weizmann Institute ...
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In this talk, we will discuss problems associated with synchronizing specific events in space and time (X-coherence), fact-checking, and mining persons, objects and contents of interest from various and heterogeneous sources including — but not limited to — the internet, social media and surveillance imagery. ...
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In this lecture we will introduce the quantum bit (qubit), the basic rules of quantum information/computing, the no-cloning principle, quantum gates for universal quantum computing; finally we will see two protocols, one for quantum teleportation, and one for quantum key distribution.
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Nowadays, as computer networks continuously increase in size and speed, making efficient use of compute and network resources becomes exceptionally challenging. At the heart of this challenge are scheduling and load balancing techniques that are expected to optimize resource usage and, in turn, minimize costs. ...
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In this thesis, we show how geometry, and specifically parametric freeform geometry, can be used to solve manufacturing related problems. This thesis deals with both additive manufacturing (specifically 3D printing) and the more traditional (subtractive manufacturing) machining process. The first topic handled is the representation ...
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Named-entity Recognition (NER) is an important task in the NLP field, and is widely used to solve many challenges. However, in many scenarios, not all of the entities are explicitly mentioned in the text. Sometimes they could be inferred from the context or from other ...
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In bidirectional heuristic search the search proceeds from both the start and the goal simultaneously.The state of the art in bidirectional search has changed significantly a very short time period; we now can answer questions about unidirectional and bidirectional search that until very recently we ...
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We propose a principled approach to integrating GPU memory with an OS page cache. We design GAIA, a weakly-consistent page cache that spans CPU and GPU memories. GAIA enables the standard mmap system call to map files into the GPU address space, thereby enabling data-dependent ...
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Rapid advances in data-driven applications over recent years have intensified the need for efficient mechanisms capable of real-time monitoring and detecting arbitrarily complex patterns in massive data streams. Complex event processing (CEP) is a prominent technology widely employed for performing this task in many areas, ...
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Inverse problems appear in many applications, such as image deblurring, inpainting and super-resolution. The common approach to address them is to design a specific algorithm (or recently - a deep neural network) for each problem. The Plug-and-Play (P&P) framework, which has been recently introduced, allows ...
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The wide usage of smartphones encourages users to ubiquitously and constantly interact with web applications like microblogs and search engines. Examples of atomic interactions, referred as micro-actions, include posing a query, sending a textual message, sharing a photo etc. Analysis of micro-actions is beneficial for ...
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In the Maximum Carpool Matching problem we seek for the best way a group of people can share their ride based on their personal preferences (music, smoking, etc...). Submodularity is a property of set functions. The problem of maximizing a submodular function appears in many ...
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Patch matching and local treatment of images has proven to be a successful strategy for problems such as image denoising, inpainting, super-resolution, image editing and the list could go on and on. Naturally, the size of the patch is a crucial parameter of the patch ...
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Feed-forward CNNs trained for image transformation problems rely on loss functions that measure the similarity between the generated image and a target image. Most of the common loss functions assume that these images are spatially aligned and compare pixels at corresponding locations. However, for many ...
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The mathematical study of social and information networks has historically centered around generative models for such networks (preferential attachment, the Chung-Lu random graph model, Kronecker graphs, etc.). This talk proposes distribution-free models of social and information networks - novel classes of graphs that capture all ...
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Rich engagement data can shed light on how people interact with online content and how such interactions may be determined by the content of the page. In this work, we investigate a specific type of interaction, backtracking, which refers to the action of scrolling back ...
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Recent years have seen the emergence of new kinds of software including deep learning, programmable computer networks, and blockchains. Unfortunately, these systems have been shown to suffer from critical safety and security errors, affecting their wider adoption. The goal of my research is to develop ...
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The chest X-ray scan is by far the most commonly performed radiological examination for screening and diagnosis of many cardiac and pulmonary diseases. It is also one of the hardest to interpret, with disagreement rating of around 30% even for experienced radiologists. At Zebra, we ...
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With the increase in malicious activity over the Internet, it has become extremely important to build tools for automatic detection of such activity. There have been attempts to use machine learning to detect network attacks, but the difficulty in obtaining positive (attack) examples, led to ...
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Search systems are often focused on providing relevant results for the "now", assuming both corpora and user needs that focus on the present. However, many corpora today reflect significant longitudinal collections ranging from 20 years of the Web to hundreds of years of digitized newspapers ...
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The round complexity of zero-knowledge protocols is a long-standing open question, yet to be settled under standard assumptions. So far, the question has appeared equally challenging for relaxations such as weak zero-knowledge and witness hiding. Protocols satisfying these relaxed notions under standard assumptions have at ...
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The CS Computer Communication Lab (LCCN) invites you to an exposure evening to communication networks - to get to know the laboratory activity, the research and the projects it offers and the team that leads them, to listen to lectures and take part in discussions ...
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CS Labs: Systems and Software Development Laboratory (SSDL), Cyber and Computer Security Laboratory (CYBER), The Laboratory for Computer Communication and Networking (LCCN) invite you to visit the Yearly Project Fair on IoT, Android, Ransomware and Networks. The fair will be held on Tuesday, January 22, ...
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Neural Networks have been shown to be remarkably resistant to label noise. This means that you can train a network using a data set that contains a significant fraction of wrongly-labelled samples, and the network will still be able to accurately predict the label for ...
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The question whether one can recover the shape of a geometric object from its Laplacian spectrum (‘hear the shape of the drum’) is a classical problem in spectral geometry with a broad range of implications and applications. While theoretically the answer to this question is ...
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The rapid increase in the popularity of cryptocurrencies brought with it not only questions regarding the quality of the technology itself, but also the economic phenomena surrounding them. Bitcoin in particular has proven itself to be a very volatile commodity~[Baek and Elbeck, Applied Economics 2015], ...
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Given a set of points in a metric space, the Closest Pair problem asks to find a pair of distinct points in the set with the smallest distance. In this talk, we address the fine-grained complexity of this problem which has been of recent interest. ...
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Stream frequency measurements are fundamental in many data stream applications such as financial data trackers, intrusion-detection systems, and network monitoring. Typically, recent data items are more relevant than old ones, a notion we can capture through a sliding window abstraction. This paper considers a generalized ...
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How can we capture effectively the information expressed in multiple texts? How can we allow people, as well as computer applications, to easily explore it? The current semantic NLP pipeline typically ends at the single sentence or text level, putting the burden on applications to ...
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The driving force behind convolutional and recurrent networks — two of the most successful deep learning architectures to date — is their expressive power. Despite its wide acceptance and vast empirical evidence, formal analyses supporting this belief are scarce. The primary notions for formally reasoning ...
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A model which mimics the programming operation of memory cells was first presented by Bunte and Lapidoth. Under this paradigm we assume that cells are programmed sequentially and individually. The programming process is modeled as transmission over a channel, while it is possible to read ...
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A central object in optimal stopping theory is the single-choice prophet inequality for independent, identically distributed random variables: Given a sequence of random variables X_1,…,X_n drawn independently from a distribution F, the goal is to choose a stopping time τ so as to maximize α ...
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Widely recognized as the inventor of digital cash, David is also known for other fundamental innovations in cryptography, including privacy and secure election technology. David is currently leading the Elixxir blockchain project, a private, scalable platform capable of processing a high volume of payments, messages ...
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As technology becomes highly integrated into nearly every aspect of life, and in many cases is indispensable, maintaining relative hand functionality is crucial. A transradial amputation is a partial amputation of the arm below the elbow that can greatly impede one’s ability to perform every ...
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We tackle the problem of multiple image alignment and 3D reconstruction under extreme noise. Photographs acquired in scenes with large intensity variations or in scattering media have significant spatial variance in signal-to-noise-ratio (SNR), where in some image regions it is significantly below the level current ...
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Can we program computers in our native tongue? This idea, termed natural language programming (NLPRO), has attracted attention almost since the inception of computers themselves. From the point of view of software engineering (SE), efforts to program in natural language (NL) have relied thus far ...
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We consider the problem of anomaly detection in images, and present a new detection technique. Given a sample of images, all known to belong to a ``normal'' class (e.g., dogs), we show how to train a deep neural model that can detect out-of-distribution images (i.e., ...
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In the era of “Big Code”, research is being conducted into automating the understanding of computer programs. Most of the current works borrow techniques from natural language processing and deep learning, which have been successful recently, attempting to process the code directly or using syntactic ...
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Private information retrieval (PIR) is a technique of retrieving data from servers in a distributed storage system (DSS), without revealing the identity of the data to the servers. A scheme that achieves the PIR property is referred to as a PIR protocol and is characterized ...
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It is no secret that online companies, hospitals, credit-card companies and governments hold massive datasets composed of our sensitive personal details. Information from such datasets is often released using some privacy preserving heuristics, which have been repeatedly shown to fail. That is why in recent ...
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Understanding deep learning calls for addressing three fundamental questions: expressiveness, optimization and generalization. Expressiveness refers to the ability of compactly sized deep neural networks to represent functions capable of solving real-world problems. Optimization concerns the effectiveness of simple gradient-based algorithms in solving non-convex neural network ...
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n the function-inversion problem, an algorithm gets black-box access to a function $f:[N] \to [N]$ and takes as input a point $y \in [N]$, along with $S$ bits of auxiliary information about $f$. After running for time $T$, the algorithm must output an $x \in ...
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Hardware security of integrated circuits (ICs) is a significant concern in many emerging market segments, such as intelligent transportation, innovative health care, sophisticated security systems, and smart energy applications. In particular, modern side-channel attacks that exploit information leaked by physical IC implementation pose a serious ...
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Programming languages are a tool for human thought, expression, and work yet they are principally designed using mathematical and engineering techniques. In this talk, I will describe how our group has applied human-centered design techniques --- interviews, participatory design exercises, and qualitative analysis of developer ...
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