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ICA
2010
Springer
13 years 6 months ago
Binary Sparse Coding
We study a sparse coding learning algorithm that allows for a simultaneous learning of the data sparseness and the basis functions. The algorithm is derived based on a generative m...
Marc Henniges, Gervasio Puertas, Jörg Bornsch...
KDD
2006
ACM
122views Data Mining» more  KDD 2006»
14 years 5 months ago
Tensor-CUR decompositions for tensor-based data
Motivated by numerous applications in which the data may be modeled by a variable subscripted by three or more indices, we develop a tensor-based extension of the matrix CUR decom...
Michael W. Mahoney, Mauro Maggioni, Petros Drineas
FGR
2004
IEEE
126views Biometrics» more  FGR 2004»
13 years 9 months ago
Trainable Videorealistic Speech Animation
We describe how to create with machine learning techniques a generative, videorealistic, speech animation module. A human subject is first recorded using a videocamera as he/she u...
Tony Ezzat, Gadi Geiger, Tomaso Poggio
CIKM
2008
Springer
13 years 7 months ago
Learning a two-stage SVM/CRF sequence classifier
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...
Guilherme Hoefel, Charles Elkan