180 search results - page 10 / 36 » Parallel Algorithms for Singular Value Decomposition |
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AAAI
2011
13 years 9 months ago
2011
Recently, a number of researchers have proposed spectral algorithms for learning models of dynamical systems—for example, Hidden Markov Models (HMMs), Partially Observable Marko...
CORR
2008
Springer
14 years 9 months ago
2008
Springer
Hidden Markov Models (HMMs) are one of the most fundamental and widely used statistical tools for modeling discrete time series. In general, learning HMMs from data is computation...
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EUROPAR
2009
Springer
15 years 4 months ago
2009
Springer
With the increasing use of large image and video archives and high-resolution multimedia data streams in many of today’s research and application areas, there is a growing need f...
ICIP
2009
IEEE
14 years 7 months ago
2009
IEEE
Subspace-based methods rely on dominant element selection from second order statistics. They have been extended to tensor processing, in particular to tensor data filtering. For t...
CORR
2010
Springer
14 years 9 months ago
2010
Springer
Recently popularized randomized methods for principal component analysis (PCA) efficiently and reliably produce nearly optimal accuracy -- even on parallel processors -- unlike the...