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INTERSPEECH
2010
13 years 4 months ago
Investigation of full-sequence training of deep belief networks for speech recognition
Recently, Deep Belief Networks (DBNs) have been proposed for phone recognition and were found to achieve highly competitive performance. In the original DBNs, only framelevel info...
Abdel-rahman Mohamed, Dong Yu, L. Deng
NN
2000
Springer
152views Neural Networks» more  NN 2000»
13 years 9 months ago
A neural network theory of proportional analogy-making
A neural network model that can simulate the learning of some simple proportional analogies is presented. These analogies include, for example, (a) red-square:red-circle yellow-sq...
Nilendu G. Jani, Daniel S. Levine
ICCV
2009
IEEE
15 years 2 months ago
Level Set Segmentation with Both Shape and Intensity Priors
We present a new variational level-set-based segmentation formulation that uses both shape and intensity prior information learned from a training set. By applying Bayes’ rule...
Siqi Chen and Richard J. Radke
ICML
2006
IEEE
14 years 10 months ago
Permutation invariant SVMs
We extend Support Vector Machines to input spaces that are sets by ensuring that the classifier is invariant to permutations of subelements within each input. Such permutations in...
Pannagadatta K. Shivaswamy, Tony Jebara
ICML
2005
IEEE
14 years 10 months ago
Semi-supervised graph clustering: a kernel approach
Semi-supervised clustering algorithms aim to improve clustering results using limited supervision. The supervision is generally given as pairwise constraints; such constraints are...
Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Ray...