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» Bounds for Functions of Dependent Risks
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NIPS
2004
15 years 1 months ago
Experts in a Markov Decision Process
We consider an MDP setting in which the reward function is allowed to change during each time step of play (possibly in an adversarial manner), yet the dynamics remain fixed. Simi...
Eyal Even-Dar, Sham M. Kakade, Yishay Mansour
FOCS
2002
IEEE
15 years 4 months ago
Testing Juntas
We consider the problem of testing functions for the property of being a k-junta (i.e., of depending on at most k variables). Fischer, Kindler, Ron, Safra, and Samorodnitsky (J. Co...
Eldar Fischer, Guy Kindler, Dana Ron, Shmuel Safra...
JMLR
2010
103views more  JMLR 2010»
14 years 6 months ago
Regret Bounds and Minimax Policies under Partial Monitoring
This work deals with four classical prediction settings, namely full information, bandit, label efficient and bandit label efficient as well as four different notions of regret: p...
Jean-Yves Audibert, Sébastien Bubeck
TSP
2010
14 years 6 months ago
Compressed sensing performance bounds under Poisson noise
Abstract--This paper describes performance bounds for compressed sensing (CS) where the underlying sparse or compressible (sparsely approximable) signal is a vector of nonnegative ...
Maxim Raginsky, Rebecca Willett, Zachary T. Harman...
AI
2011
Springer
14 years 6 months ago
Bounded approximate decentralised coordination via the max-sum algorithm
In this paper we propose a novel approach to decentralised coordination, that is able to efficiently compute solutions with a guaranteed approximation ratio. Our approach is base...
Alex Rogers, Alessandro Farinelli, Ruben Stranders...