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Events for April 25, 2017
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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-seminarWebCast 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
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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
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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
