Colloquia and Seminars

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Computer Science events calendar in HTTP ICS format for of Google calendars, and for Outlook.

Academic Calendar at Technion site.

Upcoming Colloquia & Seminars

  • ceClub: Securing Internet Routing from the Ground Up

    Speaker:
    Michael Schapira (Hebrew University of Jerusalem)
    Date:
    Wednesday, 28.6.2017, 11:30
    Place:
    EE Meyer Building 861

    The Internet's communication infrastructure (TCP/IP, DNS, BGP, etc.) is alarmingly insecure, as evidenced by many high-profile incidents. I will illustrate the challenges en route to securing the Internet, and how these can be overcome, by focusing on the Internet's, arguably, biggest security hole: the vulnerability of Internet routing to traffic hijacking attacks.

    Bio:
    Michael Schapira is an associate professor at the School of Computer Science and Engineering, the Hebrew University of Jerusalem. He is also the scientific co-leader of the Fraunhofer Cybersecurity Center at Hebrew University. His research interests focus on the protocols/mechanisms that make the Internet tick (e.g., for routing, traffic management). He is interested in the design and analysis of practical (Inter)network architectures and protocols with provable guarantees (failure-resilience, optimality, security, incentive compatibility, and beyond). He is also broadly interested in the the interface of computer science, economics, and game theory (e.g., dynamic interactions in economic and computational environments, incentive-compatible computation, computational auctions, and more).

  • Probabilistic Reasoning Meets Heuristic Search

    Speaker:
    Rina Dechter - SPECIAL GUEST LECTURE - Note unusual day and time
    Date:
    Wednesday, 28.6.2017, 11:30
    Place:
    Room 337 Taub Bld.
    Affiliation:
    Donald Bren School of Information and Computer Sciences, UC Irvine
    Host:
    Benny Kimelfeld

    Graphical models, including constraint networks, Bayesian networks, Markov random fields and influence diagrams, have become a central paradigm for knowledge representation and reasoning in Artificial Intelligence, and provide powerful tools for solving problems in a variety of application domains, including coding and information theory, signal and image processing, data mining, learning, computational biology, and computer vision. Although past decades have seen considerable progress in algorithms in graphical models, many real-world problems are of such size and complexity that they remain out of reach. Advances in exact and approximate inference methods are thus crucial to address these important problems with potential impact across many computational disciplines. Exact inference is typically NP-hard, motivating the development of approximate and anytime techniques. After summarizing the main principles behind the AND/OR search guided by heuristics based on variational inference (e.g., weighted mini-bucket and cost-shifting schemes) for graphical model queries, I will focus on recent work for solving the marginal map task, a query that combines, and generalizes, optimization and summations queries and is far harder than both. The emerging solvers aim for anytime behavior that generate not only an approximation that improves with time, but also upper and lower bounds which become tighter with more time. Short Bio. ========== Rina Dechter's research centers on computational aspects of automated reasoning and knowledge representation including search, constraint processing, and probabilistic reasoning. She is a Chancellor's Professor of Computer Science at the University of California, Irvine. She holds a Ph.D. from UCLA, an M.S. degree in applied mathematics from the Weizmann Institute, and a B.S. in mathematics and statistics from the Hebrew University in Jerusalem. She is an author of Constraint Processing published by Morgan Kaufmann (2003), and Reasoning with Probabilistic and Deterministic Graphical Models: Exact Algorithms by Morgan and Claypool publishers, 2013, has co-authored close to 200 research papers, and has served on the editorial boards of: Artificial Intelligence, the Constraint Journal, Journal of Artificial Intelligence Research (JAIR), and Journal of Machine Learning Research (JMLR). She is a Fellow of the American Association of Artificial Intelligence 1994, was a Radcliffe Fellow 2005-2006, received the 2007 Association of Constraint Programming (ACP) Research Excellence Award, and she is a 2013 ACM Fellow. She has been Co-Editor- in-Chief of Artificial Intelligence since 2011. She is also co-editor with Hector Geffner and Joe Halpern of the book Heuristics, Probability and Causality: A Tribute to Judea Pearl, College Publications, 2010. ======================================== Refreshments will be served from 11:15 Lecture starts at 11:30

  • Exposure to Virtual Reality Course Event

    Exposure to Virtual Reality Course Event

    Date:
    Wednesday, 28.6.2017, 12:30
    Place:
    CS Taub Lobby

    The Geometric Image Processing Laboratory (GIP) and the Center for Graphics and Geometric Computing (CGGC) invite you to a special event of exposure and early registration to their joint course: Virtual and Augmented Reality.

    The event will be held as part of the End of Year party, on Wednesday, June 28, 2017, between 12:30-14:30at the CS Taub Lobby.

    More details in the attached poster.

    You are all invited!

  • Generalizations of the Cardinality Estimation Problem and Applications to Computer Networks

    Speaker:
    Aviv Yehezkel, Ph.D. Thesis Seminar
    Date:
    Wednesday, 28.6.2017, 13:00
    Place:
    Taub 601
    Advisor:
    Prof. Reuven Cohen

    Sketch-based streaming algorithms allow efficient processing of big data. These algorithms use small fixed-size storage to store a summary ("sketch") of the input data, and use probabilistic algorithms to accurately estimate the desired quantity. A fundamental streaming problem is "cardinality estimation": given a very long stream of elements, the goal is to estimate the number of distinct elements. This is a well-known problem with numerous applications for network monitoring, security, query optimization, query execution progress, etc. This Ph.D. research focuses on several generalizations of the cardinality estimation problem. We propose new streaming algorithms, analyze their efficiency and statistical performance, and use them for solving interesting network monitoring problems. In this talk, two main results will be presented. The first is a novel estimator to the cardinality of set intersection between two sets, which is shown to outperform all previously known estimators. The second is a new framework for the cardinality estimation problem. This framework consists of a novel sketch, and a family of algorithms that use this sketch to accurately estimate the cardinality of any set expression.

  • The True Difference Between Emulation and Paravirtualization of High-Throughput I/O Devices

    Speaker:
    Arthur Kiyanovski, M.Sc. Thesis Seminar
    Date:
    Wednesday, 28.6.2017, 13:00
    Place:
    Taub 701
    Advisor:
    Prof. Dan Tsafrir

    Machine virtualization has grown in popularity in recent years with the growth of cloud computing. Virtual machines use virtual I/O devices to perform their I/O. Nowadays paravirtual I/O devices are the most popular type of virtual I/O devices due to their high performance and interposition capabilities. However paravirtual I/O devices also have disadvantages. Users need to install device drivers for paravirtual devices whenever they switch hypervisors, and hypervisor providers need to implement device drivers for all operating systems. Emulated I/O devices also allow interposition, and do not have the disadvantages of paravirtual I/O devices as they are designed to work with the device drivers of the physical devices they emulate. These device drivers come preinstalled in all major operating systems, which makes the task of switching hypervisors much easier for the users. And since the device drivers have already been written for the physical devices being emulated, hypervisor providers need not implement device drivers for emulated devices. However emulated I/O devices achieve substantially lower performance than paravirtual ones, which makes them unusable in many real world scenarios. Previous works state that the main reason for the performance difference between paravirtual and emulated I/O devices is the larger amount of exits caused by the latter. To test this claim we created a model that estimates the maximum possible throughput that can be achieved by QEMU’s emulated e1000 NIC, when taking the throughput of the paravirtual virtio-net NIC and adding the overhead of e1000’s extra exits. This model predicts a throughput difference of only 1.13X in favor of virtio-net, which is very different from the 20X throughput difference achieved in practice. This result led us to search for reasons other than exits that could explain this difference. In this work we present differences between QEMU’s virtio-net and e1000 other than exits, which we found contributing to the throughput gap between the two. For each difference we propose an improvement to e1000, inspired by virtio-net’s implementation. We then use the sidecore paradigm to reduce part of the exits caused by e1000 to further improve the throughput of e1000. We were able to reduce the throughput gap between vritio-net and e1000 down to 1.2X when the guest runs on a single core and to 1.25X on a dual core with our sidecore. Our results show that emulated I/O devices can achieve performace that is close to that of paravirtual ones, which might make emulated devices the better choice when flexibilty is more important than best performance.

  • Probabilistic Pursuits on Graphs

    Speaker:
    Michael Amir, M.Sc. Thesis Seminar
    Date:
    Thursday, 29.6.2017, 11:30
    Place:
    Taub 301
    Advisor:
    Prof. Alfred M. Bruckstein.

    We consider a discrete system of "ant-like" agents which pursue each other on the vertices of a graph environment. Visually reminiscent of a trail of ants, the agents emerge one by one at equal time intervals from a source vertex s and pursue each other by greedily attempting to close the distance to their immediate predecessor, the agent that emerged just before them from s, until they arrive at the destination point t. Such pursuits have been investigated before in the continuous setting and in discrete time when the underlying environment is a regular grid graph. In both these settings the agents' walks provably converge to a shortest path between s and t. Furthermore, assuming a certain natural probability distribution over the move choices of the agents on the grid (in case there are multiple shortest paths between an agent and its predecessor), the walks converge to the uniform distribution over all shortest paths from s to t. We study, more generally, the evolution of such systems over a general graph environment G. We will exhibit surprising connections to topology, convex geometry and graph theory. For example, if every three pairwise intersecting disks of G have a non-empty (shared) intersection, the agents' walks are guaranteed to converge to the uniform distribution over all shortest paths.

  • Theory Students Meeting

    Theory Students Meeting

    Date:
    Sunday, 2.7.2017, 14:30
    Place:
    Taub 301

    Theory graduate students will present their field of study alongside some of the problems they are conducting research on.

    More details in the attached poster.

    Everyone is welcome to attend, no special background is assumed.

    Refreshments will be served.

  • Project Fair in IoT and Android

    Project Fair in IoT and Android

    Date:
    Tuesday, 4.7.2017, 12:30
    Place:
    CS Taub Lobby

    On Tuesday, July 4th, 2017, the Systems and Software Development Laboratory (SSDL) will hold a project Fair on IoT and Android, presenting the newest and most inspiring projects presented by the developing teams.

    You are all invited!

    Following are the presenting projects:

    IOT

    BreakFast
    Have your favorite breakfast ready when you wake up
    i-Chess
    Magic Chess board
    LarMe
    Intelligent Anti-Theft System
    3D Pong
    Modern Pong played on a 3D LED Cube
    Pancake Printer
    Draws your perfect customized Pancake
    Tanks
    Multiplayer game with autonomous tanks
    i-Carry
    Smart luggage that escorts you, controlled with your phone or gesture recognition
    Voice maze
    A smart car that helps to improve word spelling

    ANDROID

    iChant
    A smart chanter made for those who want to play a wind instrument
    BiPo
    Automatically check and keep track of attendance to courses.
    Bialik
    A mobile platform to encourage your inner poet.
    BookASeat
    You will always have a seat in the library waiting for you.
    Learnguage
    Learn a new language using pictures of your surroundings.
    SportTime
    Keeps track of sporting events schedules and be notified on any delays.
    TestMe
    Your personal tutor that will help you study for exams.
    Toudly
    Connect with people around you to discuss (very) local events.
    Smart Parking
    Finds the best route to the nearest parking and to the office
    Smart Supermarket
    Remembers the client preferences

    YEARLY PROJECT

    UP&GO
    An easy to use scheduler
    Athenizer
    Lets you zoom in and out the code – to inflate or deflate the code to be more understandable
    Smart City Accessibility
    Reviews locations based on their accessibility
    Mambo
    Helps hearing impaired people to drive
    Bracelet
    Emergency Medical Treatment

  • IBM Quantum Experience: Prospects for universal quantum computing in the marketplace

    Speaker:
    Yehuda Naveh - SPECIAL GUEST LECTURE
    Date:
    Tuesday, 4.7.2017, 14:30
    Place:
    Room 337 Taub Bld.
    Affiliation:
    IBM Haifa Reserch Lab
    Host:
    Tal Mor

    IBM recently released IBM Quantum Experience, a freely accessible programming interface to its 5-bit universal quantum computer, accompanied by a 16-bit beta version, both set on the IBM Cloud. I will describe the science and technology behind this milestone event. I will then present IBM's further vision for quantum computing in the marketplace, in terms of hardware, software stack, potential applications, and algorithms. Short Bio: ========== Yehuda Naveh got his B.Sc. in physics and math, M.Sc. in experimental condensed matter physics, and Ph.D. in theoretical condensed matter physics, all from Hebrew University of Jerusalem. After four years at Stony Brook University, working on electronic properties of semiconductors and superconductors, he joined IBM Research - Haifa, where he has been working on a spectrum of applications, including leading the quantum computation related activity at IBM Haifa. ======================================= Refreshments will be served from 14:15 Lecture starts at 14:30

  • Theory Seminar: Randomized Online Matching in Regular Graphs

    Speaker:
    David Wajc (Carnegie Mellon University)
    Date:
    Wednesday, 5.7.2017, 12:30
    Place:
    Taub 201

    In this talk, we will discuss the classic bipartite matching problem in the online setting, first introduced in the seminal work of Karp, Vazirani and Vazirani (STOC '90). Specifically, we consider the problem for the well-studied class of regular graphs. Matching in this class of graphs was studied extensively in the offline setting. In the online setting, an optimal deterministic algorithm, as well as efficient algorithms under stochastic input assumptions were known. In this work, we present a novel randomized algorithm with competitive ratio tending to one on this family of graphs, under adversarial arrival order. Our main result is an algorithm which achieves competitive ratio 1-O(\sqrt{\log d} / \sqrt{d}) in expectation on d-regular graphs, and thus the problem becomes easier for randomized algorithms as d increases (for deterministic algorithms, the optimal competitive ratio is known to decrease as d increases, and tends to 1-1/e). In contrast, we show that all previously-known online algorithms, such as the generally worst-case optimal RANKING algorithm of Karp et al., are restricted to a competitive ratio strictly bounded away from one, even as d grows. Moreover, we show the converge rate of our algorithm's competitive ratio to one is nearly tight, as no algorithm achieves competitive ratio better than 1-O(1 / \sqrt{d}). Finally, we show that our algorithm yields a similar competitive ratio with high probability, as well as guaranteeing each vertex a probability of being matched tending to one.

    Joint work with Ilan R. Cohen (Hebrew University of Jerusalem).

  • Pixel Club: Visual Looming Approach for Autonomous Navigation

    Speaker:
    Daniel Raviv​ ​and ​Juan David Yepes (CS, Technion)
    Date:
    Wednesday, 5.7.2017, 14:30
    Place:
    Room 337 Taub Bld.

    Have you ever wondered about “order amidst chaos” in a “crazy” intersection where drivers, bikers and pedestrians manage to cross it without collisions?​ This talk is about low level visual cues that can help to explain the sensing and actions of different non-colliding moving vehicles and people. The talk focuses on one of the cues, called “Visual Looming” that can be measured and act-upon locally at the moving agent level.​ ​In this presentation we will explain the initial motivation for the research, i.e., the desire to explain behaviors of school of fish and flock of birds, followed by simulated agents that self organize behavior-wise. We will share underlying principles, and how to use them to affect heading and speed. Both simulated and experimental results will be shown.​ ​The visual looming is a time-based scalar tha​​t can be obtained using raw data from one moving camera in stationary and/or changing (i.e., moving objects) environments. It does not need 3D reconstruction, and no knowledge on the direction of motion of the camera or other moving objects is needed. The value of looming is independent of the observer’s rotation.​ ​Together with another visual cue, the angular velocity, it can be used to “map” space in terms of time, using spheres and cylinders that expand and shrink, depending on specific relative motions. This cue along with others that we briefly introduce (we call them visual field invariants) remind us of cues that are used by humans to achieve basic visual tasks. In addition, logarithmic retina and fixated motion reduce the number of computations.​ ​Experiments show that it is texture independent, and can also be measured using defocusing, change in brightness, expansion of objects in the image, etc. We have used it in real driving (basic level only), and with 6DOF simulator. The looming value can also be measured by other sensors. ​​

    ​Bio​:
    Daniel Raviv is currently a visiting professor at the Technion, researching at the Computer Science Faculty, and teaching at the Electrical Engineering Faculty.​ ​He received his B.Sc. and M.Sc. degrees from the Technion, and his Ph.D. from Case Western Reserve University in Cleveland, Ohio. He is a professor at ​​Florida Atlantic University where he is the Director of the Innovation and Entrepreneurship Lab. In the past he served as the assistant provost for innovation.​Dr.Raviv taught at Johns Hopkins University and the University of Maryland, and was a visiting researcher at the National Institute of Standards and Technology (NIST) as part of a group that developed a driverless car for the US Army (HUMVEE; 65 mph). His interest are in autonomous vehicles, active vision, teaching and learning Innovative thinking, and how to teach innovatively. Daniel developed a fundamentally different methodology for innovative problem solving a.k.a. “Eight Keys to Innovation.” He is the author of five books: Three on learning innovative thinking and two on teaching in visual and intuitive ways. He is a co-holder of a Guinness world record. ​Juan David Yepes is currently visiting the Computer Science Faculty at the Technion. He is working on Computer Vision research and simulations for vision-based navigation of multi-agent autonomous vehicles.​ ​He has a BS and MEE in Electrical Engineering and an MBA in Globlal Business. Currently he is the CEO of Industrias Terrigeno, and preparing for his Ph.D. studies. He taught specialization courses on NGN Networks. Juan has 18-year of experience in the Telecom Industry in Latin America as a senior manager in planning and operations of IP/Metro Ethernet Networks and Optical Networks. His interest interests are in Computer Vision and Autonomous Systems as well as Embedded Systems, and in developing Unity3D simulations.

  • Sampling-on-Demand in SDN

    Speaker:
    Evgeny Moroshko, M.Sc. Thesis Seminar
    Date:
    Wednesday, 5.7.2017, 15:00
    Place:
    Taub 601
    Advisor:
    Prof. Reuven Cohen

    Sampling is an expensive network resource, because switches and routers are able to sample only a small fraction of the traffic they receive. Modern switches and routers perform uniform packet sampling, which has several important drawbacks: (i) the same flow might be unnecessarily sampled multiple times in different switches; (ii) all the flows traversing a switch whose sampling module is activated are sampled in the same rate; (iii) the sampling rate is fixed, even if the volume of the traffic changes. In this work, we propose a sampling on-demand monitoring framework. The proposed framework, presented as a component of SDN (Software Defined Network), adds a Sampling Management Module to the SDN controller. This module allows the controller to determine the sampling rate of each flow at each switch according to the monitoring goals of the network operator, while taking into account the monitoring capabilities of the switch. As part of the proposed framework, we define a new optimization problem called SAP (Sampling Allocation Problem), which has to be solved by the Sampling Management Module in order to maximize the sampling total utility. We present online and offline algorithms for solving this problem. We also present three real network management applications, executed over Mininet, which are shown to significantly benefit from the proposed framework.

  • Coding Schemes for Non-Volatile Memories

    Speaker:
    Michal Horovitz, Ph.D. Thesis Seminar
    Date:
    Thursday, 6.7.2017, 14:30
    Place:
    Taub 601
    Advisor:
    Prof. Eitan Yaakobi and Prof. Tuvi Etzion

    Flash memories is a non-volatile technology that is both electrically programmable and electrically erasable. It incorporates a set of cells maintained at a set of levels of charge to encode information. While raising the charge level of a cell is an easy operation, reducing the charge level requires the erasure of the whole block to which the cell belongs, which is a slow operation and damages the life-time of the device. I will present some of our results regarding two coding schemes which overcome the common errors in flash memories. The first scheme I will present is Write-Once Memory (WOM) codes which allow to write multiple times to the memory without decreasing the levels of the cells. The second scheme is Rank Modulation (RM) in which the information is carried by the relative ranking of the cells' charge levels and not by their absolute values. This scheme provides a more efficient programming of cells and is more robust to charge leakage. I will also mention the reconstruction problem which is come up in the DNA-storage, another non-volatile technology.

  • On Visibility and Point Clouds

    Speaker:
    Nati Kligler, M.Sc. Thesis Seminar
    Date:
    Tuesday, 11.7.2017, 11:30
    Place:
    Taub 601
    Advisor:
    Prof. A. Tal

    We introduce the concept of visibility detection within a point set to new domains. Specifically, we show that a simple representation of an image as a 3D point cloud lets us use visibility detection in classical image processing tasks, improving state-of-the-art results. Given an image, each pixel is represented as a feature point, a viewpoint is set, and points that are visible to the viewpoint are detected. What does it mean for a point to be visible? Although this question has been widely studied within computer graphics, it has never been regarded when the point set consists of feature vectors (rather than a real scene). We show that the answer to this question reveals unique information about the image, enabling us to modify state-of-the-art algorithms and improve their own results. As proof of concept, we demonstrate this idea within three applications: text image binarization, document unshadowing and stippling-style illustration.

  • CGGC Seminar: Efficient Collision Detection and Avoidance for Tree Structures using Sweep-based BVH

    Speaker:
    Myung Soo Kim (Seoul National University)
    Date:
    Sunday, 16.7.2017, 12:30
    Place:
    Room 337 Taub Bld.

    We present an interactive tree modeling and deformation system that supports an efficient collision detection and avoidance using a bounding volume hierarchy of sweep surfaces. Starting with conventional tree models (given as meshes), we convert them into sweep surfaces and deform their branches interactively while detecting and avoiding collisions with many other branches.

    Multiple tree models (sharing the same topology) can be generated with great ease using the sweep-based approach, and they can serve as a basis for the generation of a multiparameter family of trees. Using a similar technique, we can also develop a compact modeling scheme for human lung anatomy (with lung lobes, bronchial trees, and pulmonary blood vessels), and demonstrate a plausible deformation (with collision detection and avoidance) for the whole anatomical structure in an interactive speed.