Y
Yishay Mansour
Researcher at Tel Aviv University
Publications - 546
Citations - 30407
Yishay Mansour is an academic researcher from Tel Aviv University. The author has contributed to research in topics: Regret & Upper and lower bounds. The author has an hindex of 80, co-authored 511 publications receiving 26984 citations. Previous affiliations of Yishay Mansour include Technion – Israel Institute of Technology & IBM.
Papers
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Journal ArticleDOI
Almost k -wise independence versus k -wise independence
TL;DR: In this paper, it was shown that for any (e, k)-wise independent distribution there exists some k-wise independent distributions whose statistical distance is at least nO(k)
Proceedings Article
Convergence of Optimistic and Incremental Q-Learning
Eyal Even-Dar,Yishay Mansour +1 more
TL;DR: It is shown that incremental Q-learning converges, in the limit, to the optimal policy, and can be viewed as derandomization of the e-greedy Q- learning.
Journal ArticleDOI
Nonstochastic Multi-Armed Bandits with Graph-Structured Feedback
Noga Alon,Noga Alon,Nicolò Cesa-Bianchi,Claudio Gentile,Shie Mannor,Yishay Mansour,Ohad Shamir +6 more
TL;DR: A partial-information model of online learning, where a decision maker repeatedly chooses from a finite set of actions, and observes some subset of the associated losses, is presented and studied.
Proceedings Article
Learning Multiple Tasks using Shared Hypotheses
Koby Crammer,Yishay Mansour +1 more
TL;DR: This work considers a setting where a very large number of related tasks with few examples from each individual task, and considers learning a small pool of shared hypotheses, which derives VC dimension generalization bounds for the model based on the number of tasks, shared hypothesis and the VC dimension of the hypotheses class.
Posted Content
Efficient Nash Computation in Large Population Games with Bounded Influence
Michael Kearns,Yishay Mansour +1 more
TL;DR: In this paper, the authors introduce a general representation of large-population games in which each player s influence ON the others is centralized and limited, but may otherwise be arbitrary, which significantly generalizes the class known as congestion games in a natural way.