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» Algorithms for Non-negative Matrix Factorization
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STOC
2009
ACM
133views Algorithms» more  STOC 2009»
14 years 9 months ago
Numerical linear algebra in the streaming model
We give near-optimal space bounds in the streaming model for linear algebra problems that include estimation of matrix products, linear regression, low-rank approximation, and app...
Kenneth L. Clarkson, David P. Woodruff
DAGSTUHL
2006
13 years 10 months ago
Using fast matrix multiplication to solve structured linear systems
Structured linear algebra techniques enable one to deal at once with various types of matrices, with features such as Toeplitz-, Hankel-, Vandermonde- or Cauchy-likeness. Following...
Éric Schost, Alin Bostan, Claude-Pierre Jea...
KES
2010
Springer
13 years 7 months ago
Extracting Principal Components from Pseudo-random Data by Using Random Matrix Theory
We develop a methodology to grasp temporal trend in a stock market that changes year to year, or sometimes within a year depending on numerous factors. For this purpose, we employ ...
Mieko Tanaka-Yamawaki
ICML
2009
IEEE
14 years 9 months ago
Matrix updates for perceptron training of continuous density hidden Markov models
In this paper, we investigate a simple, mistakedriven learning algorithm for discriminative training of continuous density hidden Markov models (CD-HMMs). Most CD-HMMs for automat...
Chih-Chieh Cheng, Fei Sha, Lawrence K. Saul
TIP
2010
154views more  TIP 2010»
13 years 7 months ago
Projective Nonnegative Graph Embedding
—We present in this paper a general formulation for nonnegative data factorization, called projective nonnegative graph embedding (PNGE), which 1) explicitly decomposes the data ...
Xiaobai Liu, Shuicheng Yan, Hai Jin