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» Preprocessing of Intractable Problems
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UAI
2003
13 years 11 months ago
Learning Generative Models of Similarity Matrices
Recently, spectral clustering (a.k.a. normalized graph cut) techniques have become popular for their potential ability at finding irregularlyshaped clusters in data. The input to...
Rómer Rosales, Brendan J. Frey
ECAI
2010
Springer
13 years 11 months ago
Unsupervised Layer-Wise Model Selection in Deep Neural Networks
Abstract. Deep Neural Networks (DNN) propose a new and efficient ML architecture based on the layer-wise building of several representation layers. A critical issue for DNNs remain...
Ludovic Arnold, Hélène Paugam-Moisy,...
ICML
2010
IEEE
13 years 11 months ago
Learning Efficiently with Approximate Inference via Dual Losses
Many structured prediction tasks involve complex models where inference is computationally intractable, but where it can be well approximated using a linear programming relaxation...
Ofer Meshi, David Sontag, Tommi Jaakkola, Amir Glo...
CORR
2010
Springer
136views Education» more  CORR 2010»
13 years 10 months ago
Optimally Sparse Frames
Frames have established themselves as a means to derive redundant, yet stable decompositions of a signal for analysis or transmission, while also promoting sparse expansions. Howe...
Peter G. Casazza, Andreas Heinecke, Felix Krahmer,...
CORR
2006
Springer
71views Education» more  CORR 2006»
13 years 10 months ago
Wreath Products in Stream Cipher Design
The paper develops a novel approach to stream cipher design: Both the state update function and the output function of the corresponding pseudorandom generators are compositions of...
Vladimir Anashin