Random Walk Approach to Regret Minimization
Hariharan Narayanan ⋅ Sasha Rakhlin
2010 Poster
Abstract
We propose a computationally efficient random walk on a convex body which rapidly mixes to a time-varying Gibbs distribution. In the setting of online convex optimization and repeated games, the algorithm yields low regret and presents a novel efficient method for implementing mixture forecasting strategies.
Chat is not available.
Successful Page Load