[Colloquium] REMINDER: 5/15 TTIC Colloquium: Afonso Bandeira, New York University

[Mary Marre via Colloquium]

When:     Monday, May 15th at 11:00 a.m.

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

Who:       Afonso Bandeira, New York University

Title:       On Phase Transitions for Spiked Random Matrix and Tensor Models


Abstract: A central problem of random matrix theory is to understand
the eigenvalues of spiked random matrix models, in which a prominent
eigenvector (or low rank structure) is planted into a random matrix.
These distributions form natural statistical models for principal
component analysis (PCA) problems throughout the sciences, where the
goal is often to recover or detect the planted low rank structured. In
this talk we discuss fundamental limitations of statistical methods to
perform these tasks and methods that outperform PCA at it. Emphasis
will be given to low rank structures arising in Synchronization
problems.

Time permitting, analogous results for spiked tensor models will also be
discussed.



Host: Nathan Srebro <nati 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, May 8, 2017 at 4:48 PM, Mary Marre <mmarre at ttic.edu> wrote:

> When:     Monday, May 15th at 11:00 a.m.
>
> Where:    TTIC, 6045 S. Kenwood Avenue, 5th Floor, Room 526
>
> Who:       Afonso Bandeira, New York University
>
> Title:       On Phase Transitions for Spiked Random Matrix and Tensor
> Models
>
>
> Abstract: A central problem of random matrix theory is to understand
> the eigenvalues of spiked random matrix models, in which a prominent
> eigenvector (or low rank structure) is planted into a random matrix.
> These distributions form natural statistical models for principal
> component analysis (PCA) problems throughout the sciences, where the
> goal is often to recover or detect the planted low rank structured. In
> this talk we discuss fundamental limitations of statistical methods to
> perform these tasks and methods that outperform PCA at it. Emphasis
> will be given to low rank structures arising in Synchronization
> problems.
>
> Time permitting, analogous results for spiked tensor models will also be
> discussed.
>
>
>
> Host: Nathan Srebro <nati 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 <(773)%20834-1757>*
> *f: (773) 357-6970 <(773)%20357-6970>*
> *mmarre at ttic.edu <mmarre at ttic.edu>*
>
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