SCIENTIFIC PROGRAMS AND ACTIVITIES

May 29, 2017

THE FIELDS INSTITUTE FOR RESEARCH IN MATHEMATICAL SCIENCES

Thematic Program on Statistical Inference, Learning, and Models for Big Data, January to June, 2015

February 9 11 , 2015
Workshop on Optimization and Matrix Methods in Big Data
Organizing Committee

Stephen Vavasis (Chair),Anima Anandkumar,
Petros Drineas, Michael Friedlander,
Nancy Reid, Martin Wainwright

On-line registration is now closed.
On-site registration available during workshop.

Registration fees: $150, students and PDF: $50

List of Workshop Participants Reimbursement information for funded participants
Accommodation in Toronto Information for speakers
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Program


Tentative Schedule

Monday February 9

8:00

Coffee and Registration

9:15-9:30

Welcoming Remarks

9:30-10:30

Petros Drineas (via WebEx), Rensselaer Polytechnic Institute
RandNLA: Randomization in Numerical Linear Algebra

10:30-11:00

Coffee

11:00-12:00

Alexandre d'Aspremont, École Normale Supérieure

12:00-2:00

Lunch
2:00-3:00
Inderjit S. Dhillon, University of Texas
Sparse inverse covariance estimation for a million variables
3:00-3:30

Tea

3:30-4:30

Maryam Fazel, University of Washington
Convex regularization with the Diversity norm: properties and algorithms
4:30-5:30
Michael Friedlander, University of California, Davis

5:30

Cash Bar Reception
Tuesday February 10

9:30-10:30

Animashree Anandkumar, University of California, Irvine
Spectral Methods for Generative and Discriminative Learning with Latent Variables

10:30-11:00

Coffee break

11:00-12:00

Lin Xiao, Microsoft Research
Communication-Efficient Distributed Optimization of Self-Concordant Empirical Loss

12:00-2:00

Lunch break

2:00-3:00

Ben Recht (via WebEx), University of California, Berkeley

3:00-3:30

Tea break
3:30-4:30
Tamara Kolda, Sandia National Laboratories
Computing the Largest Entries in a Matrix Product via Sampling
4:30-5:30
Yaniv Plan, University of British Columbia
The generalized lasso with non-linear measurements
Wednesday February 11

9:30-10:30

Michael Mahoney, University of California, Berkeley
Eigenvector localization, implicit regularization, and algorithmic anti-differentiation for large-scale graphs and matrix data

10:30-11:00

Coffee break

11:00-12:00

Quentin Berthet, California Institute of Technology
Statistical and Computational Tradeoffs for Sparse Principal Component Analysis

12:00-1:00

Lunch break (On-site lunch)
1:00-2:00
Po-Ling Loh, University of Pennsylvania
PDW methods for support recovery in nonconvex high-dimensional problems

2:00-3:00

Jakub Marecek, IBM Research
Coordinate Descent and Challenges therein

3:00-3:30

Tea break
3:30 -4:30
Stephen A. Vavasis, University of Waterloo


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