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ICONIP
2009
15 years 4 months ago
Tracking in Reinforcement Learning
Reinforcement learning induces non-stationarity at several levels. Adaptation to non-stationary environments is of course a desired feature of a fair RL algorithm. Yet, even if the...
Matthieu Geist, Olivier Pietquin, Gabriel Fricout
CORR
2012
Springer
196views Education» more  CORR 2012»
14 years 2 months ago
PAC-Bayesian Policy Evaluation for Reinforcement Learning
Bayesian priors offer a compact yet general means of incorporating domain knowledge into many learning tasks. The correctness of the Bayesian analysis and inference, however, lar...
Mahdi Milani Fard, Joelle Pineau, Csaba Szepesv&aa...
ICML
2006
IEEE
16 years 7 months ago
A continuation method for semi-supervised SVMs
Semi-Supervised Support Vector Machines (S3 VMs) are an appealing method for using unlabeled data in classification: their objective function favors decision boundaries which do n...
Olivier Chapelle, Mingmin Chi, Alexander Zien
ICML
2005
IEEE
16 years 7 months ago
Incomplete-data classification using logistic regression
A logistic regression classification algorithm is developed for problems in which the feature vectors may be missing data (features). Single or multiple imputation for the missing...
David Williams, Xuejun Liao, Ya Xue, Lawrence Cari...
ICML
2004
IEEE
16 years 7 months ago
Sequential skewing: an improved skewing algorithm
This paper extends previous work on the Skewing algorithm, a promising approach that allows greedy decision tree induction algorithms to handle problematic functions such as parit...
Soumya Ray, David Page