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» On fuzzy inference by the least squares method
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CSDA
2010
157views more  CSDA 2010»
13 years 5 months ago
Robust estimation of constrained covariance matrices for confirmatory factor analysis
Confirmatory factor analysis (CFA) is a data anylsis procedure that is widely used in social and behavioral sciences in general and other applied sciences that deal with large qua...
E. Dupuis Lozeron, M. P. Victoria-Feser
GECCO
2006
Springer
150views Optimization» more  GECCO 2006»
13 years 9 months ago
Evaluation relaxation using substructural information and linear estimation
The paper presents an evaluation-relaxation scheme where a fitness surrogate automatically adapts to the problem structure and the partial contributions of subsolutions to the fit...
Kumara Sastry, Cláudio F. Lima, David E. Go...
ICCV
2009
IEEE
1957views Computer Vision» more  ICCV 2009»
14 years 10 months ago
Robust Visual Tracking using L1 Minimization
In this paper we propose a robust visual tracking method by casting tracking as a sparse approximation problem in a particle filter framework. In this framework, occlusion, corru...
Xue Mei, Haibin Ling
GECCO
2007
Springer
162views Optimization» more  GECCO 2007»
13 years 12 months ago
Learning noise
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
Michael D. Schmidt, Hod Lipson
BMCBI
2006
119views more  BMCBI 2006»
13 years 5 months ago
LS-NMF: A modified non-negative matrix factorization algorithm utilizing uncertainty estimates
Background: Non-negative matrix factorisation (NMF), a machine learning algorithm, has been applied to the analysis of microarray data. A key feature of NMF is the ability to iden...
Guoli Wang, Andrew V. Kossenkov, Michael F. Ochs