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ICML
2010
IEEE
13 years 5 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
GECCO
2005
Springer
150views Optimization» more  GECCO 2005»
13 years 10 months ago
Population-based incremental learning with memory scheme for changing environments
In recent years there has been a growing interest in studying evolutionary algorithms for dynamic optimization problems due to its importance in real world applications. Several a...
Shengxiang Yang
CVPR
2003
IEEE
14 years 6 months ago
An Efficient Approach to Learning Inhomogeneous Gibbs Model
Inhomogeneous Gibbs model (IGM) [4] is an effective maximum entropy model in characterizing complex highdimensional distributions. However, its training process is so slow that th...
Ziqiang Liu, Hong Chen, Heung-Yeung Shum
JMLR
2006
117views more  JMLR 2006»
13 years 4 months ago
On the Complexity of Learning Lexicographic Strategies
Fast and frugal heuristics are well studied models of bounded rationality. Psychological research has proposed the take-the-best heuristic as a successful strategy in decision mak...
Michael Schmitt, Laura Martignon