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NN
2007
Springer
162views Neural Networks» more  NN 2007»
15 years 2 months ago
Learning grammatical structure with Echo State Networks
Echo State Networks (ESNs) have been shown to be effective for a number of tasks, including motor control, dynamic time series prediction, and memorizing musical sequences. Howeve...
Matthew H. Tong, Adam D. Bickett, Eric M. Christia...
IJCNN
2000
IEEE
15 years 7 months ago
VC Dimension Bounds for Product Unit Networks
A product unit is a formal neuron that multiplies its input values instead of summingthem. Furthermore, it has weights acting as exponents instead of being factors. We investigate...
Michael Schmitt
UAI
2008
15 years 4 months ago
Projected Subgradient Methods for Learning Sparse Gaussians
Gaussian Markov random fields (GMRFs) are useful in a broad range of applications. In this paper we tackle the problem of learning a sparse GMRF in a high-dimensional space. Our a...
John Duchi, Stephen Gould, Daphne Koller
IDA
2010
Springer
15 years 1 months ago
Multi-dimensional data construction method with its application to learning from small-sample-sets
Insufficient training data is one of the major problems in neural network learning, because it leads to poor learning performance. In order to enhance an intelligent learning proc...
Hsiao-Fan Wang, Chun-Jung Huang
EWRL
2008
15 years 4 months ago
Bayesian Reward Filtering
A wide variety of function approximation schemes have been applied to reinforcement learning. However, Bayesian filtering approaches, which have been shown efficient in other field...
Matthieu Geist, Olivier Pietquin, Gabriel Fricout