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AI
1998
Springer
13 years 8 months ago
Model-Based Average Reward Reinforcement Learning
Reinforcement Learning (RL) is the study of programs that improve their performance by receiving rewards and punishments from the environment. Most RL methods optimize the discoun...
Prasad Tadepalli, DoKyeong Ok
TIP
2011
217views more  TIP 2011»
13 years 3 months ago
Contextual Object Localization With Multiple Kernel Nearest Neighbor
—Recently, many object localization models have shown that incorporating contextual cues can greatly improve accuracy over using appearance features alone. Therefore, many of the...
Brian McFee, Carolina Galleguillos, Gert R. G. Lan...
SECON
2007
IEEE
14 years 3 months ago
Self-Learning Repeated Game Framework for Distributed Primary-Prioritized Dynamic Spectrum Access
Dynamic spectrum access has become a promising approach to fully utilize the scarce spectrum resources. In a dynamically changing spectrum environment, it is very important to desi...
Beibei Wang, Zhu Ji, K. J. Ray Liu
ML
2012
ACM
385views Machine Learning» more  ML 2012»
12 years 4 months ago
An alternative view of variational Bayes and asymptotic approximations of free energy
Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...
Kazuho Watanabe
ICML
2010
IEEE
13 years 10 months ago
Improved Local Coordinate Coding using Local Tangents
Local Coordinate Coding (LCC), introduced in (Yu et al., 2009), is a high dimensional nonlinear learning method that explicitly takes advantage of the geometric structure of the d...
Kai Yu, Tong Zhang