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» Gaussian Processes in Machine Learning
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99
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NIPS
2008
15 years 1 months ago
Analyzing human feature learning as nonparametric Bayesian inference
Almost all successful machine learning algorithms and cognitive models require powerful representations capturing the features that are relevant to a particular problem. We draw o...
Joseph Austerweil, Thomas L. Griffiths
FLAIRS
2004
15 years 1 months ago
Using Previous Experience for Learning Planning Control Knowledge
Machine learning (ML) is often used to obtain control knowledge to improve planning efficiency. Usually, ML techniques are used in isolation from experience that could be obtained...
Susana Fernández, Ricardo Aler, Daniel Borr...
76
Voted
FLAIRS
1998
15 years 1 months ago
Optimizing Production Manufacturing Using Reinforcement Learning
Manyindustrial processes involve makingparts with an assemblyof machines, where each machinecarries out an operation on a part, and the finished product requires a wholeseries of ...
Sridhar Mahadevan, Georgios Theocharous
103
Voted
ML
2002
ACM
121views Machine Learning» more  ML 2002»
15 years 5 days ago
Near-Optimal Reinforcement Learning in Polynomial Time
We present new algorithms for reinforcement learning, and prove that they have polynomial bounds on the resources required to achieve near-optimal return in general Markov decisio...
Michael J. Kearns, Satinder P. Singh
107
Voted
ESWA
2007
136views more  ESWA 2007»
15 years 13 days ago
Semantic-based facial expression recognition using analytical hierarchy process
In this paper we present an automatic facial expression recognition system that utilizes a semantic-based learning algorithm using the analytical hierarchy process (AHP). Although...
Shyi-Chyi Cheng, Ming-Yao Chen, Hong-Yi Chang, Tzu...