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ICA
2010
Springer
13 years 8 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 7 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 10 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 9 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