[Lisa_seminaires] Alexandros Dimakis, June 15th 11AM, AA6214

Junyoung Chung elecegg at gmail.com
Jeu 15 Juin 08:00:21 EDT 2017


Hi all,

we have a tea-talk today at *11AM*.
The room will be AA6214.
You can find more details in my previous email.

Best,
--Junyoung

On Sun, Jun 11, 2017 at 10:42 PM, Junyoung Chung <elecegg at gmail.com> wrote:

> Hi all,
>
> we have another tea-talk next week. This talk will be given by Professor
> Alexandros Dimakis from the University of Texas at Austin. The talk will
> take place at *AA6214* at *11AM *on June 15th (*Thursday*).
>
> Please NOTE that there is a tea-talk on 13th (*Tuesday*) by Jackie C. K.
> Cheung (McGill University) at *Z109* (Pavillon Claire-McNicoll) at *2PM*. Check
> Dima's email for more detailed information about the talk.
>
> *Alexandros' talk.*
>
> *Title: *Generative Models and Compressed Sensing
>
> *Abstract: *The goal of compressed sensing is to estimate a vector from
> an underdetermined system of noisy linear measurements, by making use of
> prior knowledge on the structure of vectors in the relevant domain. For
> almost all results in this literature, the structure is represented by
> sparsity in a well-chosen basis. We show how to achieve guarantees similar
> to standard compressed sensing but without employing sparsity at all.
> Instead, we suppose that vectors lie near the range of a generative model,
> e.g. a GAN or a VAE. We show how the problems of image inpainting and
> super-resolution are special cases of our general framework.
>
> We show how to generalize the RIP condition for generative models and that
> random gaussian measurement matrices have this property with high
> probability. A Lipschitz condition for the generative neural network is a
> key technical condition.
> We will also discuss on-going work for adding causality and distributed
> training to these models.
>
> (based on joint work with Ashish Bora, Ajil Jalal and Eric Price)
> Code: https://github.com/AshishBora/csgm
> Homepage: users.ece.utexas.edu/~dimakis
>
> *Bio:* Alex Dimakis is an Associate Professor at the ECE department,
> University of Texas at Austin. He received his Ph.D. in 2008 from UC
> Berkeley and the Diploma degree from the National Technical University of
> Athens in 2003. During 2009 he was a CMI postdoctoral scholar at Caltech. He
> received an NSF Career award, a Google faculty research award and the Eli
> Jury dissertation award. He is the co-recipient of several best paper
> awards including the joint Information Theory and Communications Society
> Best Paper Award in 2012. He is currently serving as an associate editor
> for IEEE Transactions on Information Theory. His research interests include
> information theory, coding theory and machine learning.
>
> --Junyoung
>
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