אירועים והרצאות בפקולטה למדעי המחשב ע"ש הנרי ומרילין טאוב

Complex event processing (CEP) is widely employed to detect user-defined combinations, or patterns, of events in massive streams of incoming data. Numerous applications such as healthcare, fraud detection, and more, use CEP technologies to capture critical alerts, threats, or vital notifications. This requires that the technology meet real-time detection constraints. Multiple optimization techniques have been developed to minimize the processing time for CEP, including parallelization techniques, pattern rewriting, and more. However, these techniques may not ...
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While deep neural networks (DNNs) have shown tremendous success across various computer vision tasks, including image classification, object detection, and semantic segmentation, requirements for a large number of high-quality labels obstruct the adoption of DNNs in real-life problems. Lately, researchers have proposed multiple approaches for reducing requirements to the amount or quality of these labels or even working in a fully unsupervised way. In a series of works, we study different approaches to supervision reduction ...
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A path query extracts from the input graph the pairs of vertices that constitute the endpoints of matching paths, that is, paths such that the word obtained from the edge labels belongs to a specified language. We study the computational complexity of measuring the contribution of edges and vertices to an answer of a path query. For that, we adopt the traditional Shapley value from cooperative game theory. This value has recently been suggested and ...
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יום הכוון בפקולטה למדעי המחשב תשפ"ב 2021-22 לסטודנטים חדשים יתקיים ביום שלישי, 21 באוקטובר, 2021, ויחל בשעה 10:00 במפגש טכניוני באמפיתיאטרון ע"ש קלנר ובו ישאו דברים המשנה הבכיר לנשיא, דיקן לימודי הסמכה ודיקנית הסטודנטים ויו"ר אגודת הסטודנטים בטכניון, ובין השעות 11:00-14:00 תתקיים התכנסות ומפגש פקולטי בבניין טאוב למדעי המחשב, באודיטוריום 1 בקומת הכניסה, אשר יכלול סיורים בפקולטה, קבלת כרטיס סטודנט, היכרות עם חברי הסגל האקדמי ומזכירות לימודי הסמכה וכן פגישה עם נציגי אגודת הסטודנטים, ...
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Although caching is a well-studied topic and a widely used approach, modern software cache systems still struggle to optimize their decisions for many types of environments and workloads. This talk will briefly present four of our studies trying to tackle several on-going caching challenges. The first study reexamines the FIFO vs. LRU battle, showing that modern cache systems can often benefit from the simpler FIFO policy. The second study presents an adaptivity mechanism for software ...
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A common paradigm in engineering consists of problem modeling followed by numerical optimization. Over the years, a chasm has formed between the two stages: Models are becoming more and more complicated in order to address data irregularities while numerical optimization is being delegated to an external solver, usually not designed to handle the specific problem at hand. In this thesis I focus on problems in which there exist some underlying geometric or topological structure. Such ...
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Mining complex patterns from large data sets has attracted much attention in the last few decades. A plethora of methods and algorithms have been designed for mining a variety of patterns, ranging from simple association rules and frequent itemsets to advanced graph-based structures. However, as modern applications grow dramatically more sophisticated and operate on highly multidimensional and increasingly complex data, they introduce the demand for mining even more expressive and convoluted patterns unsupported by the ...
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The removal of noise from an image is an important and fundamental task in image processing. The statistical distribution of this noise is dependent on the measuring technique and the nature of the captured image and should be considered when tackling the denoising problem at hand. In some applications, such as in night vision, astronomy and fluorescence microscopy, the images are acquired under low light conditions and the image sensor counts a small number of ...
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Learning algorithms are increasingly prevalent within consequential real-world systems, where reliability is an essential consideration: confidently deploying learning algorithms requires more than high prediction accuracy in controlled testbeds. In this talk, we will introduce recent advancements in quantile regression—a general technique for assessing the prediction uncertainty in regression problems. In the first part, we will modify quantile regression and introduce a novel loss function that drives the predictive model (e.g., a deep net) to accurately ...
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Statistical Arbitrage is one of the pillars of quantitative trading, and has long been used by hedge funds. Historically, statistical arbitrage evolved out of the simpler pairs trade strategy, in which stocks are put into pairs (a portfolio of two stocks) by fundamental or market-based similarities. When one stock in a pair outperforms the other, the under performing stock is bought long and the outperforming stock is sold short with the expectation that under performing ...
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Partially Observable Markov Decision Process (POMDPs) are notoriously hard to solve. In this work we consider online planning in partially observable domains. Solving the corresponding POMDP problem is a very challenging task, particularly in an online setting. Our key contribution is a novel algorithmic approach, Simplified Information Theoretic Belief Space Planning (SITH-BSP), which aims to speed up POMDP planning considering belief-dependent rewards, without compromising on the solution's accuracy. We do so by mathematically relating the ...
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Mechanical image stabilization using actuated gimbals enables capturing long-exposure shots without suffering from blur due to camera motion. These devices can be externally attached to any camera with no need for specialized optics, making them the most common stabilization solution; however, they are often physically cumbersome and require high amounts of power, limiting their widespread use. In particular, an alternative solution for light airborne imaging systems, which are inherently prone to motion blur due to ...
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The world is dynamic and changes over time, thus any optimization problem used to model real life problems must address this dynamic nature, taking into account the cost of changes to a solution over time. The multistage model was introduced with this goal in mind. In this model we are given a series of instances of an optimization problem, corresponding to different times, and a solution is provided for each instance. The strive for obtaining ...
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The problem of Multi-Agent Path Finding (MAPF) calls for finding a set of conflict-free paths for a fleet of agents operating in a given environment. Arguably, the state-of-the-art approach to computing optimal solutions is Conflict-Based Search (CBS). In this work we revisit the complexity analysis of CBS to provide tighter bounds on the algorithm's run-time in the worst-case. Our analysis paves the way to better pinpoint the parameters that govern (in the worst case) the ...
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פרטים והרשמה
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Solid state drives (SSDs) have gained a central role in the infrastructure of large-scale datacenters, as well as in commodity servers and personal devices. The main limitation of flash media is its inability to support update-in-place: after data has been written to a physical location, it has to be erased before new data can be written to it. Moreover, SSDs support read and write operations in granularity of pages, while erasures are performed on entire ...
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We study the following variant of the classic bin packing problem.Given a set of items of various sizes, partitioned into groups, find a packing of the items in a minimum number of identical (unit size) bins, such that no two items of the same group are assigned to the same bin. This problem, known as bin packing with clique-graph conflicts, has natural applications in storing file replicas, security in cloud computing and signal distribution. Our ...
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Inverse problems in image processing refer to a family of problems in which we aim to recover an original signal given degraded measurements of it. Various techniques and algorithms have been suggested for general inverse problems, with a special emphasis dedicated to the most prominent example -- image denoising. Recent deep neural network approaches for these tasks focus on minimizing the mean squared error (MSE) between the original and the reconstructed signals. However, in moderate ...
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We improve the message efficiency of the time-efficient construction of a "small" (i.e. universaly optimal) k-dominating set (k-DS) under the Distributed CONGEST model. This task was suggested by Kutten and Peleg as a useful primitive in constructing other time-efficient algorithms such as a minimum spanning tree. It is also useful for constructing other local (i.e. sub-diameter time) algorithms such as partitioning the network into clusters (each a rooted tree) of diameter k. We first address ...
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Despite significant progress in software testing and verification, some undesired behaviors inevitably make their way to production. It is therefore common practice to interleave logging operations into modern software. Logging operations store information about the program's execution to help debugging and diagnosing problems. Usually, the programmer decides what parts of the program's state to log. This work aims to automatically complete logging operations in a given program based on learning from logging operations in other ...
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With the recent launch of the Intel Optane memory platform, non-volatile main memory in the form of fast, dense, byte-addressable non-volatile memory has now become available. Nevertheless, designing crash-resilient algorithms and data structures is complex and error-prone, especially when caches and machine registers are still volatile and the data residing in memory after a crash might not reflect a consistent view of the program state. This talk will present different approaches and transformations that adds ...
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A new fixed (non-adaptive) recursive scheme for multigrid algorithms is introduced. Governed by a positive parameter $\kappa$ called the cycle counter, this scheme generates a family of multigrid cycles dubbed $\kappa$-cycles. The well-known $V$-cycle, $F$-cycle, and $W$-cycle are shown to be particular members of this rich $\kappa$-cycle family, which satisfies the property that the total number of recursive calls in a single cycle is a polynomial of degree $\kappa$ in the number of levels of ...
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Model robustness to bias is often determined by the generalization on carefully designed out-of-distribution datasets. Recent debiasing methods in natural language understanding (NLU) improve performance on such datasets by pressuring models into making unbiased predictions. An underlying assumption behind such methods is that this also leads to the discovery of more robust features in the model’s inner representations. We propose a general probing-based framework that allows for post-hoc interpretation of biases in language models, and ...
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The inability to inspect metabolic activities within distinct subcellular compartments has been a major barrier to our understanding of eukaryotic cell metabolism. Previous work addressed this challenge by analyzing metabolism in isolated organelles, which grossly bias metabolic activity. Here, we developed a method for inferring physiological metabolic fluxes and metabolite concentrations in mitochondria and cytosol based on isotope tracing experiments performed with intact cells. This is made possible by computational deconvolution of metabolite isotopic labeling ...
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Inverse problems in the field of signal processing refer to the estimation of a (clean) signal when given corrupted or partial measurements of it. In this research thesis, we focus on solving such problems, using both the traditional sparse representation model and the more recent deep neural networks approach. In a series of papers, we show how one could utilize the mathematically well-understood results of the former, to improve the common practice of the latter, ...
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A \emph{polyomino} is a shape best described as a connected set of cells in the square lattice. As part of recreational mathematics, polyominoes have seen active research since the 1950s. Simultaneously, polyominoes have been investigated in statistical physics under the name ``lattice animals,'' mainly in regards to percolation problems. One of the main points of interest is to solve the yet unanswered question of how many different polyominoes exist. Most of the focus, so far, ...
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Deduplication is a widely implemented technique in storagesystems to reduce overall storage costs, or effectively increaselogical capacity, by replacing redundant chunks of data with references. As deduplication becomes a core component of storage systems, there is an opportunity to rethink storage functions to leverage the properties of deduplication, that thelogical size of a storage system may be many multiples ofthe physical data size. Specifically, we focus on the common task of performing a search for ...
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הנכם מוזמנים להצגת פרוייקטים בקורס Matter of Perspective היום, יום ב', 12 ביולי, 2021, בין 10:00-11:30 בלובי טאוב. זהו קורס ייחודי וראשון המשותף לפקולטה למדעי המחשב ולפקולטה לארכיטקטורה ובו סטודנטים עובדים בקבוצות מעורבות במטרה לייצר מוצר פיזי בטכנולוגיות ייצור דיגיטלי, באמצעות מימוש אלגוריתם גיאומטרי. הקורס מועבר על-ידי פרופ' גרשון אלבר ופרופ' מירי בן-חן (הפקולטה למדעי המחשב), יואב שטרמן (הפקולטה לארכיטקטורה) וקספר פלוטה (מתרגל, הפקולטה למדעי המחשב).
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Consumer demand forecasting is of high importance for many e-commerce applications, including supply chain optimization, advertisement placement, and delivery speed optimization. However, reliable time series sales forecasting for e-commerce is difficult, especially during periods with many anomalies, as can often happen during pandemics, abnormal weather, or sports events. Although many time-series algorithms have been applied to the task, prediction during anomalies still remains a challenge. In this work, we hypothesize that leveraging external knowledge found ...
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Molecular lead optimization is an important task of drug discovery focusing on generating novel molecules similar to a drug candidate but with enhanced properties. Prior works focused on supervised models requiring datasets of pairs of a molecule and an enhanced molecule. These approaches require large amounts of data and are limited by the bias of the specific examples of enhanced molecules. In this Thesis, we first tackle the molecule optimization problem and present an unsupervised ...
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Binary and q-ary sequences have always been used in communication channel as the carrier or the vessel of information. In order to establish an efficient and error-free communication channel, investigations on the properties of sequences are crucial. The property that we will investigate in this seminar is the reconstruction capability of binary sequences in particular from its subsequences. This is called the Sequence Reconstruction Problem. The problem considers a communication scenario where the sender transmits ...
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Many natural language inference (NLI) datasets contain biases that allow models to perform well by only using a biased subset of the input, without considering the remainder features. For instance, models are able to make a classification decision by only using the hypothesis, without learning the true relationship between it and the premise. These structural biases lead discriminative models to learn unintended superficial features and to generalize poorly out of the training distribution. In this ...
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מעבדות הפקולטה למדעי המחשב: המעבדה לפיתוח תוכנה ומערכות (SSDL), המעבדה לסייבר ואבטחת מידע (CYBER) ותקשורת מחשבים (LCCN) מזמינות אתכם לבקר ביריד האביב של פרוייקטים בתחומי IOT, תוכנה, אפליקציות אנדרואיד, AI, סייבר, אבטחת מידע ורשתות תקשורת ובו יציגו, ידגימו ויענו על שאלות בנושא מחקרם 40 צוותי תלמידי תואר ראשון. האירוע יתקיים ביום שלישי, 29 ביוני 2021, בין השעות 12:30-14:30, בקומת הכניסה לבניין טאוב למדעי המחשב. כולם מוזמנים! הפרוייקטים המציגים
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In example-based inverse linear blend skinning (LBS), a collection of poses (e.g., animation frames) are given, and the goal is finding skinning weights and transformation matrices that closely reproduce the input. These poses may come from physical simulation, direct mesh editing, motion capture, or another deformation rig. We describe a re-formulation of inverse skinning as a problem in high-dimensional Euclidean space. The transformation matrices applied to a vertex across all poses can be thought of ...
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The first generic self-stabilizing transformer for local problems in a constrained bandwidth model is introduced. This transformer can be applied to a wide class of locally checkable labeling (LCL) problems, converting a given fault free synchronous algorithm that satisfies certain conditions into a self-stabilizing synchronous algorithm for the same problem. The resulting self-stabilizing algorithms are anonymous, size-uniform, and \emph{fully adaptive} in the sense that their time complexity is bounded as a function of the number ...
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Trusted execution environments such as secure enclaves are now available in several popular CPUs, and supported in public clouds. Enclaves can be used to efficiently shield applications against privileged adversaries, and secure sensitive data processed by them through strong isolation backed by the hardware. Yet, enclaves are not a silver bullet: they are vulnerable to unique side-channel attacks, they exhibit poor performance when system calls are invoked and when page faults occur, they lack a ...
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נציגי Vayyar יגיעו לפקולטה להדגים פתרונות טכנולוגיים מבוססי מכ"מ, ביום רביעי, 23 ביוני, 2021, בין 10:00-17:00, בלובי בניין טאוב למדעי המחשב. פרטים נוספים בכרזה המצורפת. כולכם מוזמנים!
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The rise of pre-trained language models has yielded substantial progress in the vast majority of Natural Language Processing (NLP) tasks. However, a generic approach towards the pre-training procedure can naturally be sub-optimal in some cases. Particularly, fine-tuning a pre-trained language model on a source domain and then applying it to a different target domain, results in a sharp performance decline of the eventual classifier for many source-target domain pairs. Moreover, in some NLP tasks, the ...
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Consider the sparse approximation or best subset selection problem: Given a vector y and a matrix A, find a k-sparse vector x that minimizes the residual ||Ax-y||. This sparse linear regression problem, and related variants, plays a key role in high dimensional statistics, compressed sensing, machine learning and more. In this talk we focus on the trimmed lasso penalty, defined as the L_1 norm of x minus the L_1 norm of its top k entries ...
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We introduce randomized branching as a tool for parameterized approximation and develop the mathematical machinery for its analysis. Our algorithms substantially improve the best known running times of parameterized approximation algorithms for Vertex Cover and $3$-Hitting Set for a wide range of approximation ratios. The running times of our algorithms are derived from an asymptotic analysis of a broad class of two-variable recurrence relations. Our main theorem gives a simple formula for this asymptotics. The ...
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חברת רפאל תקיים מפגש Meetup בהשתתפות גידי וייס, סמנכ"ל שיווק ופיתוח עסקי חטיבתי, שידבר על הטכנולוגיות הביטחוניות המתקדמות ביותר בעולם. המפגש יתקיים ביום רביעי, 26 במאי, 2021, בפאב נולה סוקס, חיפה, ולההשתתפות נדרשת הרשמה מראש.
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הנכם מוזמנים לאירוע הגמר של תחרות הפרוייקט המצטיין שיתקיים ביום רביעי, 16 ביוני, 2021, החל מ-12:00, הכרזת והענקת פרסים לזוכים ב-14:00, בקומת הכניסה של בניין טאוב למדעי המחשב. האירוע יתקיים במתכונת יריד פרוייקטים, ובהתאם להנחיות התו הירוק. כולם מוזמנים לבוא ולפגוש את החוקרים והמחקרים הטובים ביותר!
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Complex event processing (CEP) is employed to detect user-specified patterns of events in data streams. CEP mechanisms operate by maintaining all sets of events that can potentially be composed into a pattern match. This approach can be wasteful when many of the sets do not participate in an actual match and are therefore discarded. We present DLACEP, a novel framework that fuses deep learning with CEP to efficiently extract complex pattern matches from streams. To ...
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This talk will be about the problem of discrete constrained Willmore surfaces: discrete surfaces that have minimal total squared mean curvature while also being discretely conformally equivalent to a given input surface. The Willmore energy is a bending energy, used to model elastic behavior and measure surface smoothness. Adding the conformality constraint turns the problem into a natural extension, in 2D, of classical elastic spline modeling in 1D. This not only makes the use of ...
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Work 1: we introduce a way to adapt Nesterov's well-known scheme to accelerating stationary iterative solvers for linear systems. Compared with classical Krylov subspace acceleration methods, the proposed scheme requires more iterations, but it is trivial to implement and retains essentially the same computational cost as the unaccelerated method. An explicit formula for a fixed optimal parameter is derived in the case where the stationary iteration matrix has only real eigenvalues, based only on the ...
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A main challenge in magnetic resonance imaging (MRI) is speeding up scan time. Beyond improving patient experience and reducing operational costs, faster scans are essential for time-sensitive imaging, such as fetal, cardiac, or functional MRI, where temporal resolution is important and target movement is unavoidable, yet must be reduced. Current MRI acquisition methods speed up scan time at the expense of lower spatial resolution and costlier hardware. We introduce a practical, software-only framework, based on ...
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Playing board games is considered a major challenge for both humans and AI researchers. Because some complicated board games are quite hard to learn, humans usually begin with playing on smaller boards and incrementally advance to master larger board strategies. Most neural network frameworks that are currently tasked with playing board games neither perform such incremental learning nor possess capabilities to automatically scale up. In this work, we look at the board as a graph ...
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Scene understanding requires the extraction and representation of scene components together with their individual properties, as well relations and interactions between them. In current computer vision, there has been considerable progress in recognizing scene components (people, objects, parts), but the problem of recovering scene structure is still largely open. I will describe a model that performs scene interpretation by an iterative process, combining bottom-up and top-down networks, interacting through a symmetric bi-directional communication between them. ...
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This talk will focus on structural representations and neural models of source code. I will present a language-agnostic approach for structural language modeling (SLM) of code. This general approach obtains state-of-the-art results in a variety of tasks including code summarization, code captioning, code completion, name prediction, and edit completion, outperforming sequence models (such as textual Transformers and LSTMs) and models based on graph neural networks (GNNs). Studying the reason why GNNs do poorly compared to ...
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הנכם מוזמנים למפגש מקוון (TEAMS) עם נציגי מיקרוסופט ולשמוע מפי הסטודנטים והסטודנטיות על חוויית העבודה בחברה והשילוב בין לימודים לקריירה, מהמנהלים וצוות הגיוס על ראיונות עבודה ועוד, ביום שני, 7 ביוני,2021, 18:30. קישור למפגש יישלח לאחר הרשמה מראש.
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Neural networks have made exciting progress on unstructured 3D geometric data; which is changing the way we fundamentally approach problems in geometry processing. In this talk, I will discuss several works which facilitate 3D reconstruction from several different directions, including consolidating point clouds, estimating a globally consistent point normal orientation, and reconstructing a surface mesh. Finally, I will conclude with ongoing and future work in this direction, as well as other related areas. The lecture ...
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הנכם מוזמנים להרצאה מקוונת מפי שרי דואק, בוגרת הפקולטה וכיום Data Scientist Lead בגוגל טוקיו, יפן, על פתרונות פשוטים עבור בעיות פיתוח עסקי ללקוחות, בעזרת דטה סיינס, ביום חמישי, 3 ביוני, 2021, 16:30. קישור לפגישה בזום יישלח לאחר הרשמה מראש. פרטים נוספים בכרזה המצורפת.
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The extreme fragility of deep neural networks when presented with tiny perturbations in their inputs was independently discovered by several research groups in 2013. Due to their mysterious properties and major security implications, these adversarial examples had been studied extensively over the last eight years, but in spite of enormous effort they remained a baffling phenomenon with no clear explanation. In particular, it was not clear why a tiny distance away from almost any cat ...
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There has been extensive research on data provenance. Previous works were concerned with annotating the results of database (DB) queries with provenance information which is useful in explaining query results at various resolution levels. In this work, we track the lineage of tuples throughout their database lifetime. That is, we consider a scenario in which tuples (records) that are produced by a query may affect other tuple insertions into the DB, as part of a ...
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הנכם מוזמנים למפגש מקוון עם נציגי אינול ולשמוע מפי מהנדסי התוכנה נטע קדוש וניר בדיחי על נסיונים כמראיינים, כולל כלים, תרגול וטיפים להצלחה בשלב הטכני של ראיונות, ביום שני, 31 במאי, 2021, 18:00. קישור למפגש יישלח לאחר הרשמה מראש.
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According to Aristotle, “the whole is greater than the sum of its parts”. This statement was adopted to explain human perception by the Gestalt psychology school of thought in the twentieth century. Here, we claim that when observing a part of an object which was previously acquired as a whole, one could deal with both partial correspondence and shape completion in a holistic manner. More specifically, given the geometry of a full, articulated object in ...
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Many cryptographic APIs provide extra functionality that was not intended by the designers. In this seminar we discuss such an unintended functionality in the API of HMAC as implemented by Siemens and OpenSSL. HMAC authenticates a single message at a time with a single authentication tag. However, most HMAC implementations do not complain when extra data is added to the stream after a tag is computed. We call such primitives Incremental MACs. Though HMAC is ...
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The end of Moore's law is driving the search for new techniques to improve system performance as applications continue to evolve rapidly and computing power demands continue to rise. One promising technique is to build more intelligent compilers. Compilers map high-level programs to lower-level primitives that run on hardware. During this process, compilers perform many complex optimizations to boost the performance of the generated code. These optimizations often require solving NP-Hard problems and dealing with ...
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The counter-intuitive features of quantum mechanics make it possible to solve problems and perform tasks that are beyond the abilities of non-quantum (classical) computers and communication devices. In particular, quantum key distribution (QKD) protocols allow two participants (Alice and Bob) to achieve the classically-impossible task of generating a secret shared key even if their adversary is computationally unlimited. Unfortunately, the security promises of QKD are true only in theory; practical implementations of QKD deviate from ...
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In Modern data centers, resources are usually virtualized. Applications running on those date centers are distributed over many virtual machines. For those applications, the data centers provide software defined infrastructure services for networking, storage, and security. When software defined services are running within the same CPU as the applications, they consume CPU resources on the expanse of the applications. Moreover, the data center security can be jeopardized NVIDIA Data Center Infrastructure Processing Unit (DPU) allow ...
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נציגת אינטל המומחית לארגונומיה, תערוך סדנה בנושא ביום שני, 3 במאי, 2021, בשעה 17:00, ובה טיפים לשדרוג סביבת הלימודים מרחוק. קישור להשתתפות יישלח לאחר הרשמה מראש.
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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 visualization of multiple catheters in a patient’s heart and pinpoints exact location/orientation of a catheter. During arrythmia procedure, a 3D electro-anatomical reconstruction of the heart is built and color coded ...
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הנכם מוזמנים להרצאה בנושא חישוב קוונטי: מה זה ולמה זה מגניב?מפי דר' גדי אלכסנדרוביץ - בוגר תואר שלישי בפקולטה, חוקר במעבדת המחקר של IBM בחיפה בתחום החישוב הקוונטי וכותב הבלוג המתמטי "לא מדויק" - שתעסוק בנושא המחשבים הקוונטיים והשינויים שהם יחוללו בעתיד. ההרצאה תתקיים ביום חמישים, 29 באפריל, 17:00, בפגישת זום - קישור יישלח לאחר הרשמה מראש.
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Metabolic reprogramming is a hallmark of cancer, providing novel means to selectively target cancer cells, for precision medicine and early diagnosis. Understanding tumor-specific metabolic alterations facilitates the identification of induced dependency on specific enzymes whose inhibition selectively targets cancer cells. In addition, the altered metabolic activity of cancer cells, involving the consumption of metabolic nutrients and the secretion of byproducts from the tumor leaves metabolic traces that can be utilized for diagnostic purposes. Here, we ...
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We consider scheduling real-time jobs in the classic flow shop model. The input is a set of n jobs, each consisting of m segments to be processed on m machines in the specified order. Each job also has a release time, a due date, and a weight. The objective is to maximize the throughput, i.e., to find a subset of the jobs that have the maximum total weight and can complete processing on the m ...
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The matching task is at the heart of data integration, in charge of aligning elements of data sources. Matching is a handy tool in multiple contemporary business and commerce applications and has been investigated in the fields of databases, AI, Semantic Web, and data mining for many years. The core challenge still remains the ability to create quality algorithmic matchers, automatic tools for identifying correspondences among data concepts (e.g., database attributes). Matching problems were traditionally ...
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Recent theoretical work has shown that massively overparameterized neural networks are equivalent to kernel regressors that use Neural Tangent Kernels (NTKs). Experiments indicate that these kernel methods perform similarly to real neural networks. My work in this subject aims to better understand the properties of NTK and relate them to properties of real neural networks. In particular, I will argue that for input data distributed uniformly on the sphere NTK favors low frequency predictions over ...
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הנכם מוזמנים להשתתף בסדנה טכנולוגית מקוונת בהנחיית אביב רוזנברג, תלמיד תואר שלישי ומתרגל בפקולטה, על ניהול גרסאות עם git: איך להפסיק לפחד משינוי קוד, אשר תתקיים ביום רביעי, 21 באפריל, 2021, 17:30. פרטים נוספים על תוכנית הסדנה והרשמה מראש.
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The connection between information theoretic proof systems and cryptography has been extremely fruitful. In this thesis, we further explore this connection, showing both new limitations and opportunities. In the talk we will focus on the new opportunities and show constructions of computational relaxations of objects that are known to be essentially impossible to achieve information theoretically. In particular, we show cryptographic analogs of: (1) PCPs whose length is proportional to the witness size. (2) Instance ...
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היום הפתוח במדעי המחשב בטכניון מזמין בוגרי תואר ראשון מצטיינים מכל האוניברסיטאות להירשם ללימודי תארים מתקדמים בפקולטה למדעי המחשב בסמסטר חורף תשפ"ב. האירוע יתקיים ביום ד', 21 באפריל, 2021, בין השעות 12:30-13:45 באמצעות ZOOM: פגישה מס' 96244586510. תוכנית היום תכלול סקירה על מהלך לימודי תארים מתקדמים, על המחקר ועל החיים בפקולטה למדעי המחשב בטכניון: 12:30-12:40 דבר דיקן הפקולטה, פרופ' דן גייגר 12:40-12:55 דבר סגן הדיקן לתארים מתקדמים, פרופ' גיל ברקת 12:55-13:20 ד"ר קירה רדינסקי, יו"ר ...
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יום זרקור מקוון של חברת CISCO יתקיים ביום ב', 19 באפריל 2021, בשעה 18:00, ויכלול מפגש עם צוות הסטודנטים ו בחברה, שיספרו על העבודה בסיסקו ועל אפשרויות תעסוקה בחברה. פרטים נוספים והרשמה. כולם מוזמנים!
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In recent years, topological and geometric data analysis (TGDA) has emerged as a new and promising field for processing, analyzing and understanding complex data. Indeed, geometry and topology form natural platforms for data analysis, with geometry describing the ”shape” behind data; and topology characterizing / summarizing both the domain where data are sampled from, as well as functions and maps associated to them. In this talk, I will show how topological (and geometric ideas) can ...
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Fairness has emerged as an important concern in automated decision-making in recent years, especially when these decisions affect human welfare. In this work, we study fairness in temporally extended decision-making settings, specifically those formulated as Markov Decision Processes (MDPs). Our proposed notion of fairness ensures that each state's long-term visitation frequency is more than a specified fraction. In an average-reward MDP setting, we formulate the problem as a bilinear saddle point program and, for a ...
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32% of all global deaths in the world are caused by cardiovascular diseases. The Electrocardiogram (ECG) is a non-invasive tool to measure the electrical activity of the heart, and it is the most common test performed by cardiologists to detect heart-diseases. Analyzing ECG signals manually is a hard task. Furthermore, abnormalities in the heart may occur at any time and not necessarily in the hospital. Many attempts were made to automate this task using machine ...
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A butterfly network consists of logarithmically many layers, each with a linear number of pre-specified nonzero weights. We propose to replace a dense linear layer in any neural network by an architecture based on the butterfly network. The proposed architecture significantly improves upon the quadratic number of weights required in a standard dense layer to nearly linear with little compromise in expressibility of the resulting operator. In a collection of wide variety of experiments, including ...
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A butterfly network consists of logarithmically many layers, each with a linear number of pre-specified nonzero weights. We propose to replace a dense linear layer in any neural network by an architecture based on the butterfly network. The proposed architecture significantly improves upon the quadratic number of weights required in a standard dense layer to nearly linear with little compromise in expressibility of the resulting operator. In a collection of wide variety of experiments, including ...
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Deep learning has taken the Computer Graphics world by storm. While remarkable progress has been reported in the context of supervised learning, the state of unsupervised learning, in contrast, remains quite primitive. In this talk, we will discuss recent advances where we have combined knowledge from traditional computer graphics and image formation models to enable deep generative modeling workflows. We will describe how we have combined modeling and rendering, in the unsupervised setting, to enable ...
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הנכם מוזמנים להשתתף בסדנת Code Retreat שתתקיים בפקולטה לראשונה, במטרה לחדד את מיומנות הפיתוח ולתרגל שיטת תכנות בארבע ידיים ומקלדת אחת (Pair Programming), במהלכה המשתתפים מתרגלים כתיבת קוד בזוגות ומחדדים מיומנויות של עבודה על קוד תוך תיאום ציפיות בעבודה קבוצתית, והתמודדות עם בעיה אחת מספר פעמים אך תחת אילוצים שונים, במטרה לעורר את המחשבה, לחקור ולתרגל שיטות שונות של פיתוח תוכנה. • מתחילים עם בעיית תכנות פשוטה • עובדים בצוות עם שותף נוסף לדיון ופתרון ...
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Time-series forecasting is widely employed in a variety of domains to predict future trends, tendencies, and properties of the data. However, predicting simple data items is often not enough. Many applications are characterized by a requirement to simultaneously monitor hundreds or even thousands of data series and could benefit from recognizing future occurrences of composite patterns in advance. Despite the rising need for such functionality, this problem received limited attention in recent years. In this ...
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Many texts, especially in Chemistry and Biol-ogy, describe complex processes. To answer questions about such processes one needs to understand the interactions between the different entities and to track the state transition between the different stages of the process. In this work, we tackle this problem by learning to generate corresponding code to a text that describes a chemical reaction process and a question that asks about the process outcome in a different setup. We ...
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Anomaly detection is a technique for finding unusual patterns in the given data. The study of anomaly detection has a long history and spans multiple disciplines including engineering, machine learning, statistics and real-life applications. We consider the problem of anomaly detection in tabular data, and present a detection scheme which is based on training a multiway classification model for discriminating between dozens of transformations applied to given "normal" records. The auxiliary expertise learned by the ...
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We address the problem of predicting edit completions based on a learned model that was trained on past edits. Given a code snippet that is partially edited, our goal is to predict a completion of the edit for the rest of the snippet. We refer to this task as the Edit Completion task and present a novel approach for tackling it. The main idea is to directly represent structural edits. This allows us to model ...
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In this talk, we offer an entirely “white box’’ interpretation of deep (convolution) networks from the perspective of data compression (and group invariance). In particular, we show how modern deep layered architectures, linear (convolution) operators and nonlinear activations, and even all parameters can be derived from the principle of maximizing rate reduction (with group invariance). All layers, operators, and parameters of the network are explicitly constructed via forward propagation, instead of learned via back propagation. ...
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DNA-based storage offers significant advantages over magnetic and optical storage solutions in terms of density, durability and not requiring a constant power supply. Given current trends of cost reduction in DNA synthesis and sequencing, it is now acknowledged that within the next 10 – 15 years DNA-based storage may become a highly competitive archiving technology. The microscopic world in which the DNA molecules reside induces error patterns that are fundamentally different from their digital counterparts. ...
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יום זרקור מקוון באמצעות TEAMS של חברת NVDIA יתקיים היום, יום ב', 5 באפריל 2021, בשעה 18:30, ויכלול הרצאות טכנולוגיות קצרות, מפגש שאלות ותשובות עם מהנדסי החברה, הצעות עבודה ומידע על משרות פתוחות  
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A butterfly network consists of logarithmically many layers, each with a linear number of pre-specified nonzero weights. We propose to replace a dense linear layer in any neural network by an architecture based on the butterfly network. The proposed architecture significantly improves upon the quadratic number of weights required in a standard dense layer to nearly linear with little compromise in expressibility of the resulting operator. In a collection of wide variety of experiments, including ...
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Drug repurposing is the process of applying known drugs to treat new diseases. Successful repurposing can reduce costs and time to market as medications have already passed studies of human safety. It is an important task due to the length of time and the large cost of novel drug development. In recent years, alongside the growing resources needed for developing new drugs, large biomedical repositories are becoming available as well as the maturing technology for ...
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Using DNA molecules as a data storage volume was first introduced in the 1960s by Richard Feynman. Later, in 1990, the human genome project led to a significant progress in sequencing and assembly methods. As a result, the interest in storage solutions based on DNA molecules was increased. DNA storage enjoys major advantages over magnetic and optical storage solutions. Motivated by rising technologies for DNA sequencing, this work studies reconstruction of strings based upon their ...
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Recent advances in digital manufacturing, where computational design, materials science and engineering meet, offer whole new perspectives for tailoring mechanical properties and fabrication of material with applications as diverse as product design, architecture, engineering and art. Auxetic materials are characterized by a negative Poisson’s ratio. This means that they do not behave as usual materials. When stretched in one direction, they do not shrink in the other directions, in contrary they expand. In comparison to ...
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תלמידי תארים מתקדמים בפקולטה מוזמנים לפגישה בנושא Webinar של חברת Huawei, ביום ראשון, 21 במרס, 2021, 19:30-20:30. להשתתפות נא להירשם מראש באמצעות אימייל. פרטים נוספים
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הנכם מוזמנים להרצאה מאת דר' קירה רדינסיקי: "לחזות את העתיד - הניבוי שיציל את העולם", ביום ראשון, 21 במרס, 17:00. קישור לפגישת זום יישלח לאחר הרשמה מראש.
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This research aims to investigate the application of the Shapley value to quantify the contribution of a tuple to a query answer. The Shapley value is a widely known numerical measure in cooperative game theory and in many applications of game theory for assessing the contribution of a player to a coalition game. It has been established already in the 1950s, and is theoretically justified by being the very single wealth distribution measure that satisfies ...
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Mining complex patterns from large data sets has attracted much attention in the last few decades. A plethora of methods and algorithms have been designed for mining a variety of patterns, ranging from simple association rules and frequent itemsets to advanced graph-based structures. However, as modern applications grow dramatically more sophisticated and operate on highly multidimensional and increasingly complex data, they introduce the demand for mining even more expressive and convoluted patterns unsupported by the ...
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When matching non-rigid shapes, the regular or scale-invariant Laplace-Beltrami Operator (LBO) eigenfunctions could potentially serve as intrinsic descriptors which are invariant to isometric transformations. However, the computed eigenfunctions of two quasi-isometric surfaces could be substantially different. Such discrepancies include sign ambiguities and possible rotations and reflections within subspaces spanned by eigenfunctions that correspond to similar eigenvalues. Thus, without aligning the corresponding eigenspaces it is difficult to use the eigenfunctions as descriptors. In this talk, we ...
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In virtual setups, guest virtual machines (VMs) perform their I/O through virtual I/O devices that are implemented by the hypervisor in software. There are two major flavors of virtual I/O devices. The first is ``emulation’’, which provides an interface identical to that of some preexisting physical I/O device, thus allowing the operating system (OS) inside the VM to use the original driver of the device, as is, unaware that it is in fact virtual (implemented ...
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The Hebrew Bible (Tanach) has been extensively quoted by historical religious text and commentaries throughout history. Nowadays, many of these text resources are publicly available online. Yet, the Bible quotations within them are often partially identified if at all. Knowing the exact quotations may be highly beneficial to scholars interested in studying or investigating the Bible. We have developed and empirically analyzed a machine-learning solution for this task. End-to-end, our model is comprised of three ...
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The quest for algorithms that enable cognitive abilities is an integral part of machine learning and appears in many facets, such as virtual assistant and visual reasoning. A cognitive system requires an effective approach to extract details and nuances from the multiple sensors that pound the devices' computational engine. To this end, we propose a novel form of attention mechanism, namely Factor Graph Attention, that operates on any data utilities and differentiates useful signals from ...
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The WPA3 certification aims to secure home networks, while EAP-pwd is used by certain enterprise WiFi networks to authenticate users. Both use the Dragonfly handshake to provide forward secrecy and resistance to dictionary attacks. In this paper, we systematically evaluate Dragonfly's security. First, we audit implementations, and present timing leaks and authentication bypasses in EAP-pwd and WPA3 daemons. We then study Dragonfly's design and discuss downgrade and denial-of-service attacks. Our next and main results are ...
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תלמידי תארים מתקדמים בפקולטה מוזמנים לפגישה בנושא תוכנית ההתמחות של חברת Verizon Media, ביום שלישי, 9 במרס, 2021, 17:00. להשתתפות נא להירשם מראש. פרטים נוספים
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Clustering is a basic machine learning task. In this task, a stream of input items needs to be grouped into clusters, such that all items classified into the same cluster are closer to each other than to items classified to other clusters. Each cluster is centered around a centroid point, which may either be given as a parameter, or must be learned during the process in the case of unsupervised online learning. This work studies ...
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For nearly two millennia, the word "geometry" was synonymous with Euclidean geometry, as no other types of geometry existed. Euclid's monopoly came to an end in the 19th century, where multiple examples of non-Euclidean geometries were shown. However, these studies quickly diverged into disparate fields, with mathematicians debating the relations between different geometries and what defines one. A way out of this pickle was shown by Felix Klein in his Erlangen Programme, which proposed approaching ...
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We show a new connection between circuit lower bounds and interactive proofs in restricted computational models. Specifically, we focus on the frontier problem of whether a DNF augmented with an additional layer of parity (XOR) gates, can approximate the inner product function. We show that the existence of such a small circuit, would have unexpected general implications for interactive variants of the Data Streaming and Communication Complexity models.
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Neural models of code have shown impressive results when performing tasks such as predicting method names and identifying certain kinds of bugs. We show that these models are vulnerable to adversarial examples, and introduce a novel approach for attacking trained models of code using adversarial examples. The main idea of our approach is to force a given trained model to make an incorrect prediction, as specified by the adversary, by introducing small perturbations that do ...
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We present automata over infinite data domains and their use in program verification and repair. In particular, we discuss assume-guarantee based verification, a compositional verification method that uses automata learning in order to modularly verify the correctness of a system. Then we present Assume-Guarantee-Repair (AGR) – a framework that verifies that a program satisfies a set of properties, and repairs the program in case the verification fails. We consider communicating programs – these are simple ...
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Deep neural networks (DNN) became a common tool for solving complex tasks in various fields such as computer vision, natural language processing, and recommendation systems. Despite recent progress made in enhancing the DNN performance, there are still two major obstacles hindering the practicality of DNNs in some application: their energy-expensive deployment on embedded platforms, and their amenability to malicious adversarial perturbations. In this talk, I will overview several lines of works tackling different aspects of ...
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תחרות Hash Code 2021 של גוגל תתקיים ביום חמישי, 25 בפברואר, 2021, בין השעות: 19:30-23:45 ואתם מוזמנים להירשם ל-HUB הטכניוני עד יום רביעי, 24 בפברואר, בשעה 13:00 שעון מקומי. פרטים נוספים והרשמה קבוצת ה-HUB הטכניוני בפייסבוק
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In this work, we initiate the study of fault tolerant Max-Cut, where given an edge-weighted undirected graph G=(V,E), the goal is to find a cut S, that maximizes the total weight of edges that cross S even after an adversary removes k vertices from G. We consider two types of adversaries: an adaptive adversary that sees the outcome of the random coin tosses used by the algorithm, and an oblivious adversary that does not. For ...
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We worked on a particular case of Deep Learning where the model is too large to fit into the memory of a single commodity GPU during training. Such is the case for fine-tuning, an increasingly common technique that leverages transfer learning to dramatically expedite the training of huge, high-quality models. Critically, it holds the potential to make giant state-of-the-art models pre-trained on high-end super-computing-grade systems readily available for users that lack access to such costly ...
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While Deep learning has brought a huge advancement to computer vision, for most tasks we still need hundreds of labeled samples per class. The few-shot learning tasks attempts to alleviate the data problem by learning from 1/ 5 samples per class. We will discuss the few-shot learning domain through two of my papers. The first paper LaSO, is a SOTA augmentation mechanic for multi-label few-shot classification and was published in CVPR 2019. The second paper ...
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Our research focuses on the task of Batched Vertex Cover Reconfiguration, both in centralized and distributed systems. In this talk, I will present a centralized black-box compression scheme for reconfiguration schedules. Afterwards, I will introduce the concept of Small Separator Decomposition which can be used to compute schedules in distributed systems and show how to compute it on specific graph classes in the LOCAL model of distributed computing. Lastly, I will complement the distributed results ...
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אירוע אמזון מחקר בנושאי תוכנית ההתמחות בקניות Alexa והצגת תוכנית התמחות במחקר 2021 לסטודנטים לתארים מתקדמים במדעי המחשב יתקיים ביום חמישי, 18 בפברואר, 2021, בין השעות 14:00-15:00 . בתוכנית: 14:00 - 14:20 “Alexa can you help me shop?“ Yoelle Maarek, VP of Research, Alexa Shopping, Amazon 14:20 - 14:30 Introduction to the 2021 internship program, Liane Lewin-Eytan, Sr Mgr., Alexa Shopping, Amazon 14:30 - 15:00 Panel & Q&As session, Moderated by Iftah Gamzu, Science Mgr, ...
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A concurrency semantics (aka a memory model) for a programming language defines the allowed behaviors of multithreaded programs. For programmers, sequential consistency (i.e., standard interleaving-based semantics) is considered as the most intuitive model. However, it is too costly to implement. Designing a satisfactory substitute is highly challenging as it requires to carefully balance the conflicting desires of programmers, compilers, and hardware. In this talk I will introduce this challenge and the key ideas behind the ...
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Recent advances in computational imaging have significantly expanded our ability to image through scattering layers such as biological tissues, by exploiting the auto-correlation properties of captured speckle patterns. However, most experimental demonstrations of this capability focus on the far-field imaging setting, where obscured light sources are very far from the scattering layer. By contrast, medical imaging applications such as fluorescent imaging operate in the near-field imaging setting, where sources are inside the scattering layer. We ...
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Blending and filleting are well established operations in solid modeling and computer-aided geometric design. The creation of a transition surface which smoothly connects the boundary surfaces of two (or more) objects has been extensively investigated. In this talk, we will introduce several algorithms for the construction of, possibly heterogeneous, trivariate fillets, that support smooth filleting operations between pairs of, possibly heterogeneous, input trivariates. A volumetric fillet, consisting of one or more tensor product trivariate(s), is ...
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Malicious I/O devices might compromise the OS using DMAs. The OS therefore utilizes the IOMMU to map and unmap every target buffer right before and after its DMA is processed, thereby restricting DMAs to their designated locations. This usage model, however, is neither truly secure nor can it support multi-gigabit I/O operations. IOMMU provides protection at page granularity only, whereas DMA buffers can reside on the same page as other data leading to subpage vulnerabilities, ...
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Intelligent systems which can be deployed to explore indoor buildings on a frequent and regular basis are beneficial to personnel operating remotely for security, manufacturing, or warehouse pack-and-ship. In this talk, I will present a new minimalistic approach to indoor exploration: minimal sensing, minimal prior map knowledge, and minimal underlying geometry needed to facilitate building a full visual scene representation. Our research combines both the classical and deep learning worlds, harnessing the strengths of each, ...
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For a size parameter s: N -> N, the Minimum Circuit Size Problem (denoted by MCSP[s(n)]) is the problem of deciding whether the minimum circuit size of a given function f: {0,1}^n -> {0,1} (represented by a string of length N := 2^n) is at most a threshold s(n). A recent line of work exhibited ``hardness magnification'' phenomena for MCSP: A very weak lower bound for MCSP implies a breakthrough result in complexity theory. For ...
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In-network caching promises to improve the performance of distributed and networked applications. This is by storing so-called hot items in the network switches on-route between clients who need access to the data and the storage servers who maintain it. Since the data flows through those switches in any case, it is natural to cache hot items there. Programmable switches enable managing such caches in software, where the program gets compiled and then executed at ASIC ...
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We consider the REQUIREMENT CUT problem, where given an undirected graph G = (V, E) equipped with non-negative edge weights c , and g groups of vertices X1, . , Xg in V each equipped with a requirement ri, the goal is to find a collection of edges F in E, with total minimum weight, such that once F is removed from G in the resulting graph every Xi is broken into at least ri ...
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3D computer vision has significantly advanced over the past several decades, with modern algorithms successfully reconstructing entire urban cities. However, many questions remain unexplored, as geometric reasoning alone cannot fully infer the connections among images capturing different parts of the scene or semantic relationships between images captured at distant geographic locations. In this talk, I will present an ongoing line of research that leverages powerful deep networks to address new and exciting problems in 3D ...
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Data-driven methods are increasingly being used in domains such as fraud and risk detection, where data-driven algorithmic decision making may affect human life. The growing impact of data and data-driven systems on society makes it important that people be able to trust analytical results obtained from data-driven computations. This can be done in two complementary ways: by providing result explanations so that the user understands the computation and the basis for the observed results; and ...
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Speculative execution attacks present an enormous security threat, capable of reading arbitrary program data under malicious speculation and later exfiltrating that data over microarchitectural covert channels. This talk will describe a comprehensive hardware protection from speculative execution attacks. We will first describe Speculative Taint Tracking (STT). STT delays the execution of instructions that create covert channels until their operands are proven to be a function of non-speculative data. STT builds on a comprehensive characterization of ...
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Engineering design is a task that comes with high responsibility: A failed design may easily cause not only monetary damage but, even more importantly, injuries of users. Based on a collection of design flaws [Petroski1994], this presentation will give an overview over modern design approaches that can help to prevent these mistakes in the future. It will touch upon both the topic of conceptual errors and numerical errors. The lecture will not be recorded.
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Hyperproperties lift conventional trace properties in a way that describes how a system behaves in its entirety, and not just based on its individual traces. We generalize this notion to multi-properties, which describe the behavior of a set of systems, called a multi-model. We show that model-checking multi-properties is equivalent to model-checking hyperproperties. We introduce sound and complete compositional proof rules for model-checking multiproperties, based on approximations of the systems in the multi-model and describe ...
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Offchain networks are dominant as a solution to the scalability problem of blockchain systems, allowing users to perform payments without their recording on the chain by relying on predefined payment channels. Users together with the offchain channels form a graph, known as the offchain network topology. A pair of users can employ a payment even without a direct channel through a path of channels involving other intermediate users. The offchain topology and payment characteristics affect ...
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Most AI research focuses exclusively on the AI agent itself, i.e., given some input, what are the improvements to the agent’s reasoning that will yield the best possible output? In my research, I take a novel approach to increasing the capabilities of AI agents via the use of AI to design the environments in which they are intended to act. My methods identify the inherent capabilities and limitations of AI agents and find the best ...
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We present a new approach to the acceleration of geometric algorithms for freeform surfaces using a hierarchy of bounding volumes, including those based on the osculating toroidal patches to the surfaces. Using this approach, we revisit some non-trivial conventional geometric algorithms, including those for computing the minimum and Hausdorff distances, the intersection and self-intersection curves, and the integral properties of freeform geometric models. We demonstrate the effectiveness of torus-based geometric computation, by reporting improvement in ...
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In this talk i'll be covering several works in the topic of 3D deep learning on pointclouds for scene understanding tasks. First, I'll describe VoteNet (ICCV 2019, best paper nomination): a method for object detection from 3D pointclouds input, inspired by the classical generalized Hough voting technique. I'll then explain how we integrated image information into the voting scheme to further boost 3D detection (ImVoteNet, CVPR 2020). In the second part of my talk I'll ...
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Sketches maintain compact approximate statistics about streams of data, thereby enabling quickly answering queries regarding the data stream without having to reprocess it. In this talk we will present four different papers that studies concurrent sketches and their applications. In particular we looked at these subjects : CRDT sliding window sketch, Multi-Producers Single-Consumer Queue, Limited Associativity Caches and Cache Admission Filter . In first result we introduce the notion of sliding window CRDT sketches where ...
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Quotient spaces are a natural mathematical tool to describe a variety of algorithmic problems where different objects are to be compared while their natural symmetries are to be ignored. In particular, we will focus on graphs and sets whose symmetries are permutation of the vertices, and rigid sets whose symmetries also include rigid motions. All three data types are prevalent in computer vision/graphics and in many other applications. We will discuss two problems involving these ...
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We discretize mappings between surfaces as correspondences between checkerboard patterns derived from quad meshes. This method captures the degrees of freedom inherent in smooth maps and provides a very simple and efficient computational approach to important types of maps such as conformal or isometric maps. In particular, it enables a natural definition of discrete developable surfaces which is much more flexible in applications than previous concepts of discrete developable surfaces. We discuss geometric modeling of ...
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הנכם מוזמנים לשעת זרקור של אלביט מערכות המציגה הזדמנויות וטכנולוגיות והרצאה מפי יונתן אברהם, ר"צ פיתוח, על פתרונות ייחודיים של תקשורת נטולת-תשתיות, וכן שיחה פתוחה עם גיא איסטמטי, מנהל קשרי האקדמיה, על הזדמנויות קריירה ותהליכי גיוס.   לצפייה באמצעות תוכנת Webex יש להירשם מראש.
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A streaming algorithm is given a long sequence of items and seeks to compute or approximate some function of this sequence using a small amount of memory. A body of work has been developed over the last two decades, resulting in optimal streaming algorithms for a wide range of problems. While these algorithms are well-studied, the vast majority of them are defined and analyzed in the static setting, where the stream is assumed to be ...
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There is a growing number of tasks that work directly on point clouds. As the size of the point cloud grows, so do the computational demands of these tasks. A possible solution is to sample the point cloud first. Classic sampling approaches, such as farthest point sampling (FPS), do not consider the downstream task. A recent work showed that learning a task-specific sampling can improve results significantly. However, the proposed technique did not deal with ...
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Program synthesis is the problem of generating a program to satisfy a specification of user intent. Since these specifications are usually partial, this means searching a space of candidate programs for one that exhibits the desired behavior. The lion's share of the work on program synthesis focuses on new ways to perform the search, but hardly any of this research effort has found its way into the hands of users. We wish to use synthesis ...
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My primary goal in this fringe direction of research is to develop a simple, intuitive formal framework for the automatic representation of simplified shapes and materials that can support Hyper-Realism in a wide variety of rendering applications. I observe that with the emphasis on the physical laws in rendering systems, (1) the focus increasingly shifts away from how users perceive the virtual environment, (2) rendering becomes prohibitively difficult to realize desired global illumination effects in ...
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