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ICML
2010
IEEE
13 years 9 months ago
Variable Selection in Model-Based Clustering: To Do or To Facilitate
Variable selection for cluster analysis is a difficult problem. The difficulty originates not only from the lack of class information but also the fact that high-dimensional data ...
Leonard K. M. Poon, Nevin Lianwen Zhang, Tao Chen,...
IEAAIE
2011
Springer
12 years 12 months ago
Modeling Users of Crisis Training Environments by Integrating Psychological and Physiological Data
Abstract. This paper describes aspects of a training environment for crisis decision makers who, notoriously, operate in highly stressful and unpredictable situations. Training suc...
Gabriella Cortellessa, Rita D'Amico, Marco Pagani,...
PAMI
2010
132views more  PAMI 2010»
13 years 6 months ago
Maximum Likelihood Model Selection for 1-Norm Soft Margin SVMs with Multiple Parameters
—Adapting the hyperparameters of support vector machines (SVMs) is a challenging model selection problem, especially when flexible kernels are to be adapted and data are scarce....
Tobias Glasmachers, Christian Igel
IJCAI
2001
13 years 9 months ago
Active Learning for Class Probability Estimation and Ranking
For many supervised learning tasks it is very costly to produce training data with class labels. Active learning acquires data incrementally, at each stage using the model learned...
Maytal Saar-Tsechansky, Foster J. Provost
MA
2010
Springer
132views Communications» more  MA 2010»
13 years 6 months ago
Model selection by sequentially normalized least squares
Model selection by the predictive least squares (PLS) principle has been thoroughly studied in the context of regression model selection and autoregressive (AR) model order estima...
Jorma Rissanen, Teemu Roos, Petri Myllymäki