Colloquia and Seminars

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Academic Calendar at Technion site.

Upcoming Colloquia & Seminars

  • Multiscale Models for Image Classification and Physics with Deep Networks

    Prof. Stéphane Mallat - SPECIAL GUEST LECTURE
    Tuesday, 18.6.2019, 14:30
    Room 337 Taub Bld.
    College de France
    Prof. Alfred Bruckstein

    Approximating high-dimensional functionals with low-dimensional models is a central issue of machine learning, image processing, physics and mathematics. Deep convolutional networks are able to approximate such functionals over a wide range of applications. This talk shows that these computational architectures take advantage of scale separation, symmetries and sparse representations. We introduce simplified architectures which can be analyzed mathematically. Scale separations is performed with wavelets and scale interactions are captured through phase coherence. We show applications to image classificaiton and generation as well as regression of quantum molecular energies and modelization of turbulence flows. Short Bio.: ========== Stéphane Mallat is a French applied mathematician, Professor at College de France and Ecole Normale Superieure. He has made some fundamental contributions to the development of wavelet theory in the late 1980s and early 1990s. He has also done work in applied mathematics, signal processing, music synthesis and image segmentation. With Yves Meyer, he developed the Multiresolution Analysis (MRA) construction for compactly supported wavelets, which made the implementation of wavelets practical for engineering applications by demonstrating the equivalence of wavelet bases and conjugate mirror filters used in discrete, multirate filter banks in signal processing. He also developed (with Sifen Zhong) the Wavelet transform modulus maxima method for image characterization, a method that uses the local maxima of the wavelet coefficients at various scales to reconstruct images. He introduced the scattering transform that constructs invariance for object recognition purposes. Mallat is the author of A Wavelet Tour of Signal Processing (ISBN 012466606X), a text widely used in applied mathematics and engineering courses. He has held teaching positions at New York University, Massachusetts Institute of Technology, École polytechnique and at the Ecole normale supérieure. He is currently Professor of Data Science at College de France. ========================== Refreshments will be served from 14:15 Lecture starts at 14:30

  • Theory Seminar: Planar Diameter via Metric Compression

    Merav Parter (Weizmann Institute of Science)
    Wednesday, 19.6.2019, 12:30
    Taub 201 Taub Bld.

    We develop a new approach for distributed distance computation in planar graphs that is based on a variant of the metric compression problem recently introduced by Abboud et al. [SODA'18]. In our variant of the Planar Graph Metric Compression Problem, one is given an $n$-vertex planar graph $G=(V,E)$, a set of $S \subseteq V$ source terminals lying on a single face, and a subset of target terminals $T \subseteq V$. The goal is to compactly encode the $S\times T$ distances.

    One of our key technical contributions is in providing a compression scheme that encodes all $S \times T$ distances using $\widetilde{O}(|S|\cdot\poly(D)+|T|)$ bits\footnote{As standard, $\widetilde{O}$ is used to hide $\poly\log n$ factors.}, for unweighted graphs with diameter $D$. This significantly improves the state of the art of $\widetilde{O}(|S|\cdot 2^{D}+|T| \cdot D)$ bits. We also consider an approximate version of the problem for \emph{weighted} graphs, where the goal is to encode $(1+\epsilon)$ approximation of the $S \times T$ distances, for a given input parameter $\epsilon \in (0,1]$. Here, our compression scheme uses $\widetilde{O}(\poly(|S|/\epsilon)+|T|)$ bits. In addition, we describe how these compression schemes can be computed in near-linear time. At the heart of this compact compression scheme lies a VC-dimension type argument on planar graphs, using the well-known Sauer’'s lemma.

    This efficient compression scheme leads to several improvements and simplifications in the setting of diameter computation, most notably in the distributed setting:
    - There is an $\widetilde{O}(D^5)$-round randomized distributed algorithm for computing the diameter in planar graphs, w.h.p.
    - There is an $\widetilde{O}(D^3)+\poly(\log n/\epsilon)\cdot D^2$-round randomized distributed algorithm for computing an $(1+\epsilon)$ approximation of the diameter in weighted graphs with polynomially bounded weights, w.h.p. No sublinear round algorithms were known for these problems before.

    Joint work with Jason Li, to appear in STOC'19.

  • Pixel Club: Geometric Feature Descriptors based on Partial Differential Equations

    Robert Dachsel (Brandenburg University of Technology)
    Thursday, 20.6.2019, 13:30
    Room 337 Taub Bld.

    Abstract: One of the main tasks in three-dimensional shape analysis is to retrieve similarities between two or more non-rigid objects in terms of point-to-point correspondences. For the descriptor based approach, it is useful to construct a simplified shape representation called feature descriptor. A successful descriptor class can be motivated by physical phenomena governed by partial differential equations (PDEs). The talk shows how different types of PDEs and discretization aspects may lead to quality improvements for the feature descriptor. This will be demonstrated at the hand of a detailed evaluation of a standard shape data set.

    *PhD research under supervision of Prof. Michael Breuß

  • CGGC Seminar: Viscous Thin Films in Real Time

    Saar Raz (CS, Technion)
    Sunday, 23.6.2019, 13:30
    Room 337 Taub Bld.

    I'll discuss our novel discrete scheme for simulating viscous thin films in 2D at real-time frame rates.

    Our scheme is based on a new formulation of the gradient flow approach, that leads to a discretization based on local stencils that are easily computable on the GPU.

    I'll also discuss our recent work toward a real-time 3D scheme for simulation of the effect on meshes, based on simplifications of a previous scheme.



    Monday, 24.6.2019, 15:00
    CS Taub Lobby

    The 9th CS Research Day for graduate studies will be held on Monday, June 24, 2019 between 15:00-17:00, at the lobby of the CS Taub Building.

    Research Day events are opportunity for our graduate students to expose their researches using posters and presentations to CS faculty and all degrees students, Technion distinguished representatives and to high-ranking delegates from the hi-tech leading industry companies in Israel and abroad.

    The participating researches will be on various topics: Cryptology and Cyber, Data Centers and Clouds, Graphics, Intelligent Systems and Scientific Computation, Machine Learning and Information Retrieval, Systems and Applications, Testing and Verification, Theory of Computer Science.

    Participating is free but requires preregistration.

    More details and registration

    Students wishing to present their research are kindly requested to register here.

  • Project Fair in IoT, Software, Android Apps, AI, Cyber, Computer Security, and Networks

    Project Fair in IoT, Software, Android Apps, AI, Cyber, Computer Security, and Networks

    Tuesday, 25.6.2019, 12:30
    CS Taub Lobby

    CS Labs: Systems and Software Development Laboratory (SSDL), Cyber and Computer Security Laboratory (CYBER), The Laboratory for Computer Communication and Networking (LCCN) invite you to visit the Yearly Project Fair in IoT, Software, Android Apps, AI, Cyber, Computer Security, and Networks, including demos and presentations by 60 undergraduate teams who will answer your questions on their research.

    The event will be held on Tuesday, June 25
    , 2019, at 12:30-14:30, in the CS Taub Lobby..

    You are all invtied!

    The presenting projects.

  • CGGC Seminar: Linearly Converging Quasi Branch and Bound Algorithms for Global Rigid Registration

    Nadav Dym (Duke University)
    Wednesday, 3.7.2019, 11:30
    Taub 401 Taub Bld.

    Rigid registration is the problem of finding the optimal rigid motion and correspondence between two shapes, so that they are as similar as possible in terms of an appropriate energy.

    We will describe several popular algorithms for this problem: PCA alignment and ICP, which are very efficient but are not globally optimal, as well as sampling and branch and bound (BnB) algorithms which exhibit slow convergence but are globally optimal.

    Next we suggest our quasi BnB algorithm as an improvement upon the BnB approach. Quasi BnB replaces the linear lower bounds used in BnB algorithms with quadratic quasi-lower bounds. While quasi-lower bounds are not truly lower bounds, the Quasi-BnB algorithm is globally optimal. Our experiments show that Quasi-BnB is dramatically more efficient than BnB algorithms. Theoretically we show that quasi-BnB exhibits linear convergence -- it achieves ϵ-accuracy in O(log(1/ϵ)) time while the time complexity of other rigid registration BnB algorithms is polynomial in 1/ϵ.