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» Regret Bounds for Prediction Problems
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ALT
2010
Springer
13 years 7 months ago
Optimal Online Prediction in Adversarial Environments
: In many prediction problems, including those that arise in computer security and computational finance, the process generating the data is best modeled as an adversary with whom ...
Peter L. Bartlett
DISOPT
2010
132views more  DISOPT 2010»
13 years 5 months ago
General approximation schemes for min-max (regret) versions of some (pseudo-)polynomial problems
While the complexity of min-max and min-max regret versions of most classical combinatorial optimization problems has been thoroughly investigated, there are very few studies abou...
Hassene Aissi, Cristina Bazgan, Daniel Vanderpoote...
ORL
2008
99views more  ORL 2008»
13 years 5 months ago
Some tractable instances of interval data minmax regret problems
This paper focuses on tractable instances of interval data minmax regret graph problems. More precisely, we provide polynomial and pseudopolynomial algorithms for sets of particul...
Bruno Escoffier, Jérôme Monnot, Olivi...
JMLR
2010
103views more  JMLR 2010»
13 years 16 days 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
COLT
2010
Springer
13 years 3 months ago
An Asymptotically Optimal Bandit Algorithm for Bounded Support Models
Multiarmed bandit problem is a typical example of a dilemma between exploration and exploitation in reinforcement learning. This problem is expressed as a model of a gambler playi...
Junya Honda, Akimichi Takemura