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ECAI
2008
Springer
15 years 5 months ago
Reinforcement Learning with the Use of Costly Features
In many practical reinforcement learning problems, the state space is too large to permit an exact representation of the value function, much less the time required to compute it. ...
Robby Goetschalckx, Scott Sanner, Kurt Driessens
ICML
2010
IEEE
15 years 5 months ago
Learning Markov Logic Networks Using Structural Motifs
Markov logic networks (MLNs) use firstorder formulas to define features of Markov networks. Current MLN structure learners can only learn short clauses (4-5 literals) due to extre...
Stanley Kok, Pedro Domingos
FUIN
2006
107views more  FUIN 2006»
15 years 4 months ago
Learning Sunspot Classification
Sunspots are the subject of interest to many astronomers and solar physicists. Sunspot observation, analysis and classification form an important part of furthering the knowledge a...
Trung Thanh Nguyen, Claire P. Willis, Derek J. Pad...
ML
2006
ACM
113views Machine Learning» more  ML 2006»
15 years 4 months ago
Learning to bid in bridge
Bridge bidding is considered to be one of the most difficult problems for game-playing programs. It involves four agents rather than two, including a cooperative agent. In additio...
Asaf Amit, Shaul Markovitch
PCM
2010
Springer
183views Multimedia» more  PCM 2010»
15 years 2 months ago
Fast H.264 Encoding Based on Statistical Learning
Abstract. In this paper, we propose an efficient video coding system that applies statistical learning methods to reduce the computational cost in H.264 encoder. The proposed metho...
Chen-Kuo Chiang, Shang-Hong Lai