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Events for April 25, 2017

  • USC Stem Cell Seminar: Maurizio Pacifici, The Children's Hospital of Philadelphia

    Tue, Apr 25, 2017 @ 11:00 AM - 12:00 PM

    Alfred E. Mann Department of Biomedical Engineering

    Conferences, Lectures, & Seminars

    Speaker: Maurizio Pacifici, The Children's Hospital of Philadelphia

    Talk Title: TBD

    Series: Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research at USC Distinguished Speakers Series

    Host: USC Stem Cell

    More Info: http://stemcell.usc.edu/events

    Webcast: http://keckmedia.usc.edu/stem-cell-seminar

    Location: Eli & Edythe Broad CIRM Center for Regenerative Medicine & Stem Cell Resch. (BCC) - First Floor Conference Room

    WebCast Link: http://keckmedia.usc.edu/stem-cell-seminar

    Audiences: Everyone Is Invited

    Contact: Cristy Lytal/USC Stem Cell

    Event Link: http://stemcell.usc.edu/events

  • CommNetS seminar

    Tue, Apr 25, 2017 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars

    Speaker: Dr. Christian Grussler, Lund University

    Talk Title: Low-Rank Inducing Norms with Optimality Interpretations

    Series: CommNetS

    Abstract: This talk is on optimization problems which are convex apart from a sparsity/rank constraint. These problems are often found in the context of compressed sensing, linear regression, matrix completion, low-rank approximation and many more. Today, one of the most widely used methods for solving these problems is so-called nuclear norm regularization. Despite the nice probabilistic guarantees of this method, this approach often fails for problems with structural constraints.
    In this talk, we will present an alternative by introducing the family of so-called low-rank inducing norms as convexifiers. Each norm is the convex envelope of a unitarily invariant norm plus a rank constraint. Therefore, they have several interesting properties, which will be discussed throughout the talk. They:
    i) Give a simple deterministic test if the solution to the convexified problem is a solution to a specific non-convex problem.
    ii) Often finds solutions where the nuclear norm fails to give low-rank solutions.
    iii) Allow us to analyze the convergence of non-convex proximal splitting algorithms with convex analysis tools.
    iv) Provide a more efficient regularization than the traditional scalar multiplication of the nuclear norm.
    v) Leads to a different interpretation of the nuclear norm than the one that is traditionally presented.
    vi) In particular, all the results can be generalized to so-called atomic norms.

    Biography: Christian Grussler is a postdoc at the Department of Automatic Control at Lund University, Sweden. His current research interests include positive systems, model reduction, system identification and low-rank/sparse optimization. He received a Dipl.-Math. techn. degree (Industrial Mathematics) from TU Kaiserslautern, Germany and an M.Sc. degree (Engineering Mathematics) from Lund University in 2011. In 2017, he received a Ph.D. degree from Lund University under the guidance of Anders Rantzer and Pontus Giselsson.

    Host: Prof. Mihailo Jovanovic

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132

    Audiences: Everyone Is Invited

    Contact: Annie Yu

  • Epstein Seminar, ISE 651

    Tue, Apr 25, 2017 @ 03:00 PM - 04:50 PM

    Daniel J. Epstein Department of Industrial and Systems Engineering

    Conferences, Lectures, & Seminars

    Speaker: Dr. Alper Atamturk, Professor, UC Berkeley

    Talk Title: Combinatorial Optimization with a Probabilistic Objective

    Host: Prof. Suvrajeet Sen

    More Information: April 25, 2017_Atamturk.pdf

    Location: Ethel Percy Andrus Gerontology Center (GER) - 206

    Audiences: Everyone Is Invited

    Contact: Grace Owh