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ICML
2007
IEEE
14 years 9 months ago
2007
IEEE
Markov decision processes are an effective tool in modeling decision-making in uncertain dynamic environments. Since the parameters of these models are typically estimated from da...
ICML
2006
IEEE
14 years 9 months ago
2006
IEEE
We present a new, statistical approach to rule learning. Doing so, we address two of the problems inherent in traditional rule learning: The computational hardness of finding rule...
ICML
1999
IEEE
14 years 9 months ago
1999
IEEE
Excerpted from: Boyan, Justin. Learning Evaluation Functions for Global Optimization. Ph.D. thesis, Carnegie Mellon University, August 1998. (Available as Technical Report CMU-CS-...
GECCO
2007
Springer
14 years 3 months ago
2007
Springer
This paper presents Fuzzy-UCS, a Michigan-style Learning Fuzzy-Classifier System designed for supervised learning tasks. Fuzzy-UCS combines the generalization capabilities of UCS...
ICML
2006
IEEE
14 years 9 months ago
2006
IEEE
The Viterbi algorithm is an efficient and optimal method for decoding linear-chain Markov Models. However, the entire input sequence must be observed before the labels for any tim...