Large-scale stochastic approximation proceedures

Event Details
  • Date/Time:
    • Tuesday January 16, 2007
      10:00 am - 11:00 am
  • Location: ISyE, Room 403
  • Phone: (404) 894-2300
  • URL:
  • Email:
  • Fee(s):
    N/A
  • Extras:
Contact
Arkadi Nemirovski
ISyE
Contact Arkadi Nemirovski
404-894-2300
Summaries

Summary Sentence: Large-scale stochastic approximation proceedures

Full Summary: Adaptive gain choice for large-scale stochastic approximation procedures. The subject of this talk is a complexity analysis of a family of large-scale stochastic approximation algorithms. The methods belongs to the family of primal-dual descent algorit

Adaptive Gain Choice for Large-Scale Stochastic Approximation Procedures

GUEST LECTURER
Prof. Anatoli Iouditski

AFFILIATION
University Joseph Fourier, Grenoble, France

ABSTRACT
The subject of this talk is a complexity analysis of a family of large-scale stochastic approximation algorithms. The methods belongs to the family of primal-dual descent algorithms, introduced by Yu. Nesterov. We propose an adaptive choice of the gain sequences of the algorithm which make it possible to attain the optimal rates of convergence on wide classes of problems. We show, for instance, that if it is known a priori that the objective function is Lipschitz, the proposed algorithm attains minimax rate of convergence. Further, if the objective belongs to a "better class" of smooth functions with Lipschitz-continuous gradient, the proposed algorithm also attains the minimax rate.

Additional Information

In Campus Calendar
No
Groups

H. Milton Stewart School of Industrial and Systems Engineering (ISYE)

Invited Audience
No audiences were selected.
Categories
Seminar/Lecture/Colloquium
Keywords
Adaptive gain choice, large-scale stochastic approximation procedures
Status
  • Created By: Ruth Gregory
  • Workflow Status: Published
  • Created On: Oct 12, 2009 - 5:22pm
  • Last Updated: Oct 7, 2016 - 9:48pm