Regret Minimization
Found 4 free book(s)
Introduction to Online Convex Optimization
arxiv.orgof online learning, boosting, regret minimization in games, universal predic-tion and other related topics, have seen a plethora of introductory texts in recent years. With this note we can hardly do justice to all, but perhaps point to the location of this book in the readers’ virtual library.
Fundamentals of Decision Theory - courses.cs.washington.edu
courses.cs.washington.edu–Minimization of expected regret •Minimize expected regret = maximizing expected reward! Expected Reward (Q) •called Expected Monetary Value (EMV) in DT literature •“the probability weighted sum of possible rewards for
Practical Bayesian Optimization of Machine Learning …
proceedings.neurips.ccAlthough the EI algorithm performs well in minimization problems, we wish to note that the regret formalization may be more appropriate in some settings. We perform a direct comparison between our EI-based approach and GP-UCB in Section 4.1. 3Practical Considerations for Bayesian Optimization of Hyperparameters
Adaptive Subgradient Methods for Online Learning and ...
www.jmlr.orgtion, which significantly simplifies setting a learning rate and results in regret guarantees that are provably as good as the best proximal function that can be chosen in hindsight. We give several efficient algorithms for empirical risk minimization probl ems with common and important regu-larization functions and domain constraints.