[Colloquium] Re: REMINDER: 10/24 TTIC Colloquium: Kilian Weinberger, Cornell

[Mary Marre via Colloquium]

When:     Monday, October 24th at 11:00 a.m.

Where:    TTIC, 6045 S. Kenwood Avenue, 5th Floor, Room 526

Who:       Kilian Weinberger, Cornell

Title:     Redundancy in Deep Learning

Abstract:
Deep Learning has lead to undeniable successes all over the machine
learning landscape. In contrast to most approaches, deep networks have much
larger model sizes and often fit many more parameters than training
examples. It is now apparent that a lot of these parameters are redundant
and encode similar things. In this talk I will show how to reduce the
redundancy in deep neural networks by compressing models through weight
hashing. I will also demonstrate how to leverage redundancy to make neural
networks deeper and more accurate. Finally, I will introduce a novel neural
network architecture, which, by design, incorporates these lessons and
leads to compact models with state-of-the-art generalization properties.

Bio:
Kilian Weinberger is an Associate Professor in the Department of Computer
Science at Cornell University. He received his Ph.D. from the University of
Pennsylvania in Machine Learning under the supervision of Lawrence Saul and
his undergraduate degree in Mathematics and Computer Science from the
University of Oxford. During his career he has won several best paper
awards at ICML, CVPR, AISTATS and KDD (runner-up award). In 2011 he was
awarded the Outstanding AAAI Senior Program Chair Award and in 2012 he
received an NSF CAREER award. He is co-Program Chair for ICML 2016 and AAAI
2018. Kilian Weinberger's research focuses on Machine Learning and its
applications. In particular, he focuses on learning under resource
constraints, metric learning, machine learned web-search ranking, transfer-
and multi-task learning as well as biomedical applications and deep
learning. Before joining Cornell University, he was an Associate Professor
at Washington University in St. Louis and before that he worked as a
research scientist at Yahoo! Research in Santa Clara.


Host: Greg Shakhnarovich, *greg at ttic.edu* <greg at ttic.edu>


For more information on the colloquium series or to subscribe to the
mailing list, please see http://www.ttic.edu/colloquium.php

Mary C. Marre
Administrative Assistant
*Toyota Technological Institute*
*6045 S. Kenwood Avenue*
*Room 504*
*Chicago, IL  60637*
*p:(773) 834-1757*
*f: (773) 357-6970*
*mmarre at ttic.edu <mmarre at ttic.edu>*

On Sun, Oct 23, 2016 at 7:59 PM, Mary Marre <mmarre at ttic.edu> wrote:

> When:     Monday, October 24th at 11:00 a.m.
>
> Where:    TTIC, 6045 S. Kenwood Avenue, 5th Floor, Room 526
>
> Who:       Kilian Weinberger, Cornell
>
> Title:     Redundancy in Deep Learning
>
> Abstract:
> Deep Learning has lead to undeniable successes all over the machine
> learning landscape. In contrast to most approaches, deep networks have much
> larger model sizes and often fit many more parameters than training
> examples. It is now apparent that a lot of these parameters are redundant
> and encode similar things. In this talk I will show how to reduce the
> redundancy in deep neural networks by compressing models through weight
> hashing. I will also demonstrate how to leverage redundancy to make neural
> networks deeper and more accurate. Finally, I will introduce a novel neural
> network architecture, which, by design, incorporates these lessons and
> leads to compact models with state-of-the-art generalization properties.
>
> Bio:
> Kilian Weinberger is an Associate Professor in the Department of Computer
> Science at Cornell University. He received his Ph.D. from the University of
> Pennsylvania in Machine Learning under the supervision of Lawrence Saul and
> his undergraduate degree in Mathematics and Computer Science from the
> University of Oxford. During his career he has won several best paper
> awards at ICML, CVPR, AISTATS and KDD (runner-up award). In 2011 he was
> awarded the Outstanding AAAI Senior Program Chair Award and in 2012 he
> received an NSF CAREER award. He is co-Program Chair for ICML 2016 and AAAI
> 2018. Kilian Weinberger's research focuses on Machine Learning and its
> applications. In particular, he focuses on learning under resource
> constraints, metric learning, machine learned web-search ranking, transfer-
> and multi-task learning as well as biomedical applications and deep
> learning. Before joining Cornell University, he was an Associate Professor
> at Washington University in St. Louis and before that he worked as a
> research scientist at Yahoo! Research in Santa Clara.
>
>
> Host: Greg Shakhnarovich, *greg at ttic.edu* <greg at ttic.edu>
>
>
> For more information on the colloquium series or to subscribe to the
> mailing list, please see http://www.ttic.edu/colloquium.php
>
> Mary C. Marre
> Administrative Assistant
> *Toyota Technological Institute*
> *6045 S. Kenwood Avenue*
> *Room 504*
> *Chicago, IL  60637*
> *p:(773) 834-1757 <%28773%29%20834-1757>*
> *f: (773) 357-6970 <%28773%29%20357-6970>*
> *mmarre at ttic.edu <mmarre at ttic.edu>*
>
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