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BMCBI
2007
126views more  BMCBI 2007»
13 years 8 months ago
Including probe-level uncertainty in model-based gene expression clustering
Background: Clustering is an important analysis performed on microarray gene expression data since it groups genes which have similar expression patterns and enables the explorati...
Xuejun Liu, Kevin K. Lin, Bogi Andersen, Magnus Ra...
BIRD
2008
Springer
141views Bioinformatics» more  BIRD 2008»
13 years 9 months ago
Nested q-Partial Graphs for Genetic Network Inference from "Small n, Large p" Microarray Data
Abstract. Gaussian graphical models are widely used to tackle the important and challenging problem of inferring genetic regulatory networks from expression data. These models have...
Kevin Kontos, Gianluca Bontempi
AMAI
2004
Springer
14 years 1 months ago
Approximate Probabilistic Constraints and Risk-Sensitive Optimization Criteria in Markov Decision Processes
The majority of the work in the area of Markov decision processes has focused on expected values of rewards in the objective function and expected costs in the constraints. Althou...
Dmitri A. Dolgov, Edmund H. Durfee
CP
2006
Springer
13 years 11 months ago
Towards an Efficient SAT Encoding for Temporal Reasoning
Abstract. In this paper, we investigate how an IA network can be effectively encoded into the SAT domain. We propose two basic approaches to modelling an IA network as a CSP: one r...
Duc Nghia Pham, John Thornton, Abdul Sattar
AAAI
2006
13 years 9 months ago
Model Counting: A New Strategy for Obtaining Good Bounds
Model counting is the classical problem of computing the number of solutions of a given propositional formula. It vastly generalizes the NP-complete problem of propositional satis...
Carla P. Gomes, Ashish Sabharwal, Bart Selman