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COMPLIFE
2006
Springer
13 years 11 months ago
Set-Oriented Dimension Reduction: Localizing Principal Component Analysis Via Hidden Markov Models
We present a method for simultaneous dimension reduction and metastability analysis of high dimensional time series. The approach is based on the combination of hidden Markov model...
Illia Horenko, Johannes Schmidt-Ehrenberg, Christo...
PKDD
2001
Springer
104views Data Mining» more  PKDD 2001»
14 years 3 days ago
Data Reduction Using Multiple Models Integration
Large amount of available information does not necessarily imply that induction algorithms must use all this information. Samples often provide the same accuracy with less computat...
Aleksandar Lazarevic, Zoran Obradovic
PR
2010
129views more  PR 2010»
13 years 6 months ago
Parsimonious reduction of Gaussian mixture models with a variational-Bayes approach
Aggregating statistical representations of classes is an important task for current trends in scaling up learning and recognition, or for addressing them in distributed infrastruc...
Pierrick Bruneau, Marc Gelgon, Fabien Picarougne
QEST
2009
IEEE
14 years 2 months ago
Language-Level Symmetry Reduction for Probabilistic Model Checking
—Symmetry reduction is a technique for combating state-space explosion in model checking. The generic representatives approach to symmetry reduction uses a language-level transla...
Alastair F. Donaldson, Alice Miller, David Parker
CMSB
2008
Springer
13 years 9 months ago
Automatic Complexity Analysis and Model Reduction of Nonlinear Biochemical Systems
Kinetic models for biochemical systems often comprise a large amount of coupled differential equations with species concentrations varying on different time scales. In this paper w...
Dirk Lebiedz, Dominik Skanda, Marc Fein