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» Learning Markov Network Structure with Decision Trees
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IJAR
2010
152views more  IJAR 2010»
13 years 7 months ago
Structural-EM for learning PDG models from incomplete data
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
Jens D. Nielsen, Rafael Rumí, Antonio Salme...
BROADNETS
2004
IEEE
14 years 17 days ago
Efficient QoS Provisioning for Adaptive Multimedia in Mobile Communication Networks by Reinforcement Learning
The scarcity and large fluctuations of link bandwidth in wireless networks have motivated the development of adaptive multimedia services in mobile communication networks, where i...
Fei Yu, Vincent W. S. Wong, Victor C. M. Leung
CEC
2009
IEEE
14 years 3 months ago
Structure learning and optimisation in a Markov-network based estimation of distribution algorithm
—Structure learning is a crucial component of a multivariate Estimation of Distribution algorithm. It is the part which determines the interactions between variables in the proba...
Alexander E. I. Brownlee, John A. W. McCall, Siddh...
ACL
2010
13 years 6 months ago
Towards Relational POMDPs for Adaptive Dialogue Management
Open-ended spoken interactions are typically characterised by both structural complexity and high levels of uncertainty, making dialogue management in such settings a particularly...
Pierre Lison
NN
2010
Springer
187views Neural Networks» more  NN 2010»
13 years 3 months ago
Efficient exploration through active learning for value function approximation in reinforcement learning
Appropriately designing sampling policies is highly important for obtaining better control policies in reinforcement learning. In this paper, we first show that the least-squares ...
Takayuki Akiyama, Hirotaka Hachiya, Masashi Sugiya...