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128
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NN
2006
Springer
114views Neural Networks» more  NN 2006»
15 years 3 months ago
Modular learning models in forecasting natural phenomena
Modular model is a particular type of committee machine and is comprised of a set of specialized (local) models each of which is responsible for a particular region of the input s...
Dimitri P. Solomatine, Michael Baskara L. A. Siek
150
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JMLR
2010
143views more  JMLR 2010»
14 years 10 months ago
Incremental Sigmoid Belief Networks for Grammar Learning
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
James Henderson, Ivan Titov
156
Voted
JAIR
2002
163views more  JAIR 2002»
15 years 3 months ago
Efficient Reinforcement Learning Using Recursive Least-Squares Methods
The recursive least-squares (RLS) algorithm is one of the most well-known algorithms used in adaptive filtering, system identification and adaptive control. Its popularity is main...
Xin Xu, Hangen He, Dewen Hu
138
Voted
ICIP
2010
IEEE
15 years 1 months ago
Evolutionary games for cooperative P2P video streaming
The wide-spread use of P2P video streaming systems have introduced a large number of unnecessary traverse links leading to substantial network inefficiency. To address this proble...
Yan Chen, Beibei Wang, W. Sabrina Lin, Yongle Wu, ...
142
Voted
ML
2000
ACM
157views Machine Learning» more  ML 2000»
15 years 3 months ago
A Multistrategy Approach to Classifier Learning from Time Series
We present an approach to inductive concept learning using multiple models for time series. Our objective is to improve the efficiency and accuracy of concept learning by decomposi...
William H. Hsu, Sylvian R. Ray, David C. Wilkins