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RECOMB
2003
Springer
15 years 10 months ago
Combining phylogenetic and hidden Markov models in biosequence analysis
A few models have appeared in recent years that consider not only the way substitutions occur through evolutionary history at each site of a genome, but also the way the process c...
Adam C. Siepel, David Haussler
UAI
2008
14 years 11 months ago
Modelling local and global phenomena with sparse Gaussian processes
Much recent work has concerned sparse approximations to speed up the Gaussian process regression from the unfavorable O(n3 ) scaling in computational time to O(nm2 ). Thus far, wo...
Jarno Vanhatalo, Aki Vehtari
ROCAI
2004
Springer
15 years 3 months ago
Learning Mixtures of Localized Rules by Maximizing the Area Under the ROC Curve
We introduce a model class for statistical learning which is based on mixtures of propositional rules. In our mixture model, the weight of a rule is not uniform over the entire ins...
Tobias Sing, Niko Beerenwinkel, Thomas Lengauer
ICDM
2003
IEEE
130views Data Mining» more  ICDM 2003»
15 years 3 months ago
Information Theoretic Clustering of Sparse Co-Occurrence Data
A novel approach to clustering co-occurrence data poses it as an optimization problem in information theory which minimizes the resulting loss in mutual information. A divisive cl...
Inderjit S. Dhillon, Yuqiang Guan
PKDD
2010
Springer
129views Data Mining» more  PKDD 2010»
14 years 8 months ago
Smarter Sampling in Model-Based Bayesian Reinforcement Learning
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
Pablo Samuel Castro, Doina Precup