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ICML
1999
IEEE
16 years 11 days ago
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Sebastian Thrun, John Langford, Dieter Fox
BMCBI
2008
98views more  BMCBI 2008»
14 years 11 months ago
Empirical Bayes models for multiple probe type microarrays at the probe level
Background: When analyzing microarray data a primary objective is often to find differentially expressed genes. With empirical Bayes and penalized t-tests the sample variances are...
Magnus Åstrand, Petter Mostad, Mats Rudemo
COMPSAC
2006
IEEE
15 years 5 months ago
Design Structural Stability Metrics and Post-Release Defect Density: An Empirical Study
This paper empirically explores the correlations between a suite of structural stability metrics for object-oriented designs and post-release defect density. The investigated stab...
Mahmoud O. Elish, David C. Rine
CIBCB
2006
IEEE
15 years 5 months ago
Visualization of Support Vector Machines with Unsupervised Learning
– The visualization of support vector machines in realistic settings is a difficult problem due to the high dimensionality of the typical datasets involved. However, such visuali...
Lutz Hamel
UAI
2008
15 years 29 days ago
Knowledge Combination in Graphical Multiagent Models
A graphical multiagent model (GMM) represents a joint distribution over the behavior of a set of agents. One source of knowledge aboutagents'behaviormaycomefromgametheoretic ...
Quang Duong, Michael P. Wellman, Satinder P. Singh