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» LEO - DB2's LEarning Optimizer
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DATAMINE
2006
166views more  DATAMINE 2006»
15 years 6 months ago
Accelerated EM-based clustering of large data sets
Motivated by the poor performance (linear complexity) of the EM algorithm in clustering large data sets, and inspired by the successful accelerated versions of related algorithms l...
Jakob J. Verbeek, Jan Nunnink, Nikos A. Vlassis
ECCC
2007
99views more  ECCC 2007»
15 years 6 months ago
An Exponential Time/Space Speedup For Resolution
Satisfiability algorithms have become one of the most practical and successful approaches for solving a variety of real-world problems, including hardware verification, experime...
Philipp Hertel, Toniann Pitassi
COLT
2010
Springer
15 years 4 months ago
Open Loop Optimistic Planning
We consider the problem of planning in a stochastic and discounted environment with a limited numerical budget. More precisely, we investigate strategies exploring the set of poss...
Sébastien Bubeck, Rémi Munos
COLT
2010
Springer
15 years 4 months ago
Best Arm Identification in Multi-Armed Bandits
We consider the problem of finding the best arm in a stochastic multi-armed bandit game. The regret of a forecaster is here defined by the gap between the mean reward of the optim...
Jean-Yves Audibert, Sébastien Bubeck, R&eac...
COLT
2010
Springer
15 years 4 months ago
Following the Flattened Leader
We analyze the regret, measured in terms of log loss, of the maximum likelihood (ML) sequential prediction strategy. This "follow the leader" strategy also defines one o...
Wojciech Kotlowski, Peter Grünwald, Steven de...