ARC Colloquium/ML Seminar series: Elad Hazan - Princeton University

Event Details

Dani Denton

denton at cc dot gatech dot edu


Summary Sentence: Elad Hazan presents a talk as part of the ARC Colloquium series and co-sponsored by the Machine Learning Seminar Series

Full Summary: No summary paragraph submitted.

(Please note that the talk will be held in MiRC 102 A & B and the refreshments will be served at the talk)


Projection-free Optimization and Online Learning


Modern large data sets prohibit any super-linear time operations. This motivates the study of iterative optimization algorithms with low complexity per iteration. The computational bottleneck in applying state-of-the-art iterative methods is many times the so-called "projection step".
We consider projection-free optimization/learning that replaces projections by more efficient linear optimization steps. We describe the first linearly-converging algorithm of this type for polyhedral sets and how it gives rise to optimal-rate stochastic optimization and online learning algorithms.


Additional Information

In Campus Calendar

College of Computing, School of Computer Science, ARC

Invited Audience
Undergraduate students, Faculty/Staff, Public, Graduate students
Algorithm and Randomness Center, ARC, ARC Colloquium, machine learning
  • Created By: Dani Denton
  • Workflow Status: Published
  • Created On: Feb 6, 2015 - 12:45pm
  • Last Updated: Apr 13, 2017 - 5:20pm