[Colloquium] REMINDER: 6/6 TTIC Colloquium: Brian Ziebart, UIC

[Mary Marre]

When:     Monday, June 6th at 11:00 a.m.

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

Who:        Brian Ziebart, UIC


Title:        Supervised Machine Learning as an Adversarial Game

Abstract: A standard approach to supervised machine learning is to choose
the form of a predictor and optimize its parameters based on training
data.  Approximations of the predictor's performance measure are often
required to make the optimization problem tractable.  Instead of
approximating the performance measure and using the exact training data,
this talk introduces a supervised machine learning framework that
adversarially approximates the training data and uses the exact performance
measure.  This formulation provides flexibility for addressing sample
selection bias, the fundamental problem hindering advances in active
learning, and for inductively optimizing multivariate performance measures
like the F-measure and the discounted cumulative gain from information
retrieval and ranking tasks.

Bio: Brian Ziebart is an Assistant Professor in the Department of Computer
Science at the University of Illinois at Chicago. He received his PhD from
Carnegie Mellon University where he was also a postdoctoral fellow. He has
published over 25 articles in leading machine learning and artificial
intelligence venues, including a Best Paper at the International Conference
on Machine Learning.


Host:  Karen Livescu, klivescu at ttic.edu <klivescu 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 Mon, Jun 6, 2016 at 8:04 AM, Mary Marre <mmarre at ttic.edu> wrote:

> When:     Monday, June 6th at 11:00 a.m.
>
> Where:    TTIC, 6045 S. Kenwood Avenue, 5th Floor, Room 526
>
> Who:        Brian Ziebart, UIC
>
>
> Title:        Supervised Machine Learning as an Adversarial Game
>
> Abstract: A standard approach to supervised machine learning is to choose
> the form of a predictor and optimize its parameters based on training
> data.  Approximations of the predictor's performance measure are often
> required to make the optimization problem tractable.  Instead of
> approximating the performance measure and using the exact training data,
> this talk introduces a supervised machine learning framework that
> adversarially approximates the training data and uses the exact performance
> measure.  This formulation provides flexibility for addressing sample
> selection bias, the fundamental problem hindering advances in active
> learning, and for inductively optimizing multivariate performance measures
> like the F-measure and the discounted cumulative gain from information
> retrieval and ranking tasks.
>
> Bio: Brian Ziebart is an Assistant Professor in the Department of Computer
> Science at the University of Illinois at Chicago. He received his PhD from
> Carnegie Mellon University where he was also a postdoctoral fellow. He has
> published over 25 articles in leading machine learning and artificial
> intelligence venues, including a Best Paper at the International Conference
> on Machine Learning.
>
>
> Host:  Karen Livescu, klivescu at ttic.edu <klivescu 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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