Adaptive Online Gradient Descent
We study the rates of growth of the regret in online convex optimization. First, we show that a simple extension of the algorithm of Hazan et al eliminates the need for a priori...
Publications
2 shownOptimal Strategies and Minimax Lower Bounds for Online Convex Games
A number of learning problems can be cast as an Online Convex Game: on each round, a learner makes a prediction x from a convex set, the environment plays a loss function f, and...
Frequent Co-Authors
Researcher Info
- h-index
- 2
- Publications
- 2
- Citations
- 290
- Institution
- University of California, Berkeley
External Links
Identifiers
- ORCID
- 0000-0002-8760-3140
Impact Metrics
h-index
2
h-index: Number of publications with at least h citations each.