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COLT
2003
Springer
13 years 11 months ago
Lower Bounds on the Sample Complexity of Exploration in the Multi-armed Bandit Problem
We consider the Multi-armed bandit problem under the PAC (“probably approximately correct”) model. It was shown by Even-Dar et al. [5] that given n arms, it suffices to play th...
Shie Mannor, John N. Tsitsiklis
TCC
2010
Springer
173views Cryptology» more  TCC 2010»
14 years 2 months ago
Bounds on the Sample Complexity for Private Learning and Private Data Release
Learning is a task that generalizes many of the analyses that are applied to collections of data, and in particular, collections of sensitive individual information. Hence, it is n...
Amos Beimel, Shiva Prasad Kasiviswanathan, Kobbi N...
COLT
1993
Springer
13 years 10 months ago
Bounding the Vapnik-Chervonenkis Dimension of Concept Classes Parameterized by Real Numbers
The Vapnik-Chervonenkis (V-C) dimension is an important combinatorial tool in the analysis of learning problems in the PAC framework. For polynomial learnability, we seek upper bou...
Paul W. Goldberg, Mark Jerrum
ICML
2010
IEEE
13 years 6 months ago
Efficient Selection of Multiple Bandit Arms: Theory and Practice
We consider the general, widely applicable problem of selecting from n real-valued random variables a subset of size m of those with the highest means, based on as few samples as ...
Shivaram Kalyanakrishnan, Peter Stone
ECCC
2010
124views more  ECCC 2010»
13 years 5 months ago
Lower Bounds and Hardness Amplification for Learning Shallow Monotone Formulas
Much work has been done on learning various classes of "simple" monotone functions under the uniform distribution. In this paper we give the first unconditional lower bo...
Vitaly Feldman, Homin K. Lee, Rocco A. Servedio