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» Learning Approximate Consistencies
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165
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JMLR
2008
209views more  JMLR 2008»
15 years 4 months ago
Bayesian Inference and Optimal Design for the Sparse Linear Model
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Matthias W. Seeger
JIFS
2006
120views more  JIFS 2006»
15 years 4 months ago
Building similarity metrics reflecting utility in case-based reasoning
Fundamental to case-based reasoning is the idea that similar problems have similar solutions. The meaning of the concept of "similarity" can vary in different situations...
Ning Xiong, Peter Funk
152
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NECO
2008
170views more  NECO 2008»
15 years 4 months ago
Representational Power of Restricted Boltzmann Machines and Deep Belief Networks
Deep Belief Networks (DBN) are generative neural network models with many layers of hidden explanatory factors, recently introduced by Hinton et al., along with a greedy layer-wis...
Nicolas Le Roux, Yoshua Bengio
NCA
2006
IEEE
15 years 4 months ago
Evolutionary training of hardware realizable multilayer perceptrons
The use of multilayer perceptrons (MLP) with threshold functions (binary step function activations) greatly reduces the complexity of the hardware implementation of neural networks...
Vassilis P. Plagianakos, George D. Magoulas, Micha...
138
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IJBRA
2007
80views more  IJBRA 2007»
15 years 4 months ago
On predicting secondary structure transition
A function of a protein is dependent on its structure; therefore, predicting a protein structure from an amino acid sequence is an active area of research. Optimally predicting a ...
Raja Loganantharaj, Vivek Philip