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» Efficient and Numerically Stable Sparse Learning
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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...
NIPS
2008
13 years 8 months ago
One sketch for all: Theory and Application of Conditional Random Sampling
Conditional Random Sampling (CRS) was originally proposed for efficiently computing pairwise (l2, l1) distances, in static, large-scale, and sparse data. This study modifies the o...
Ping Li, Kenneth Ward Church, Trevor Hastie
CORR
2010
Springer
210views Education» more  CORR 2010»
13 years 7 months ago
Exploiting Statistical Dependencies in Sparse Representations for Signal Recovery
Signal modeling lies at the core of numerous signal and image processing applications. A recent approach that has drawn considerable attention is sparse representation modeling, in...
Tomer Faktor, Yonina C. Eldar, Michael Elad
SIAMMAX
2010
224views more  SIAMMAX 2010»
13 years 1 months ago
Robust Approximate Cholesky Factorization of Rank-Structured Symmetric Positive Definite Matrices
Abstract. Given a symmetric positive definite matrix A, we compute a structured approximate Cholesky factorization A RT R up to any desired accuracy, where R is an upper triangula...
Jianlin Xia, Ming Gu
JMLR
2008
188views more  JMLR 2008»
13 years 6 months ago
Maximal Causes for Non-linear Component Extraction
We study a generative model in which hidden causes combine competitively to produce observations. Multiple active causes combine to determine the value of an observed variable thr...
Jörg Lücke, Maneesh Sahani