Monthly Archives: June 2019

Optimal bound for stochastic bandits with corruption

Guest post by Mark Sellke. In the comments of the previous blog post we asked if the new viewpoint on best of both worlds can be used to get clean “interpolation” results. The context is as follows: in a STOC … Continue reading

Posted in Machine learning, Optimization, Theoretical Computer Science | 24 Comments

Amazing progress in adversarially robust stochastic multi-armed bandits

In this post I briefly discuss some recent stunning progress on robust bandits (for more background on bandits see these two posts, part 1 and part 2, in particular what is described below gives a solution to Open Problem 3 … Continue reading

Posted in Machine learning, Optimization, Theoretical Computer Science | 7 Comments