
Abstract:
We prove a central limit theorem for a class of additive processes that arise naturally in the
theory of finite horizon Markov decision problems. The main theorem generalizes a…








We give an efficient algorithm for computing a Cournot equilibrium when the producers are confined to integers, the inverse demand function is linear, and costs are quadratic. The method also…


Variational analysis has come of age. Long an elegant theoretical toolkit for variational mathematics and nonsmooth optimization, it now increasingly underpins the study of algorithms, and a rich…


Tuesday, February 4, 2014 at 4:15pm
Upson Hall, B17
ORIE Colloquium: John Duchi (UC Berkeley)  Machine Learning: a Discipline of Resource Tradeoffs
Joint colloquium with Computer Science.
How…


Tuesday, Apr 15, 2014 at 4:15 PM [.ics]
253 Rhodes Hall
Natesh Pillai
Assistant Professor, Department of Statistics
Harvard University
Category: ORIE Colloquium Seminars


Friday, February 28, 2014 at 12:00pm
Frank H. T. Rhodes Hall, 253
Ezra's Round Table/Systems Seminar: Matthew Ferringer (The Aerospace Corporation)  Challenges and Success on the Way to…




CAM Colloquium: Javier Pena (Carnegie Mellon)  On the Role of Separation in Convex Optimization
Friday, February 22, 2013 at 3:30pm
Frank H. T. Rhodes Hall, 655
Separating hyperplane theorems are…


Tuesday, April 17 at 4:15pm
Frank H.T. Rhodes Hall, 253
We analyze the efficiency of particular Markov chain methods used in Bayesian statistics, giving some of the first meaningful bounds on the…


Friday, April 6 at 12:00pm
Frank H.T. Rhodes Hall, 253
Optimization of multidisciplinary systems is critical as slight performance improvements can provide significant benefits over the…


Kenneth Regan
Department of Computer Science and Engineering
University at Buffalo
Friday, November 16, 2012
Skill Inference and Chess Cheating Detection from Big Data
We describe a…




The behaviour of any physical system is governed by its dynamical equations. Much of physics is concerned with discovering these dynamical equations and understanding their implications. It is…
