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NIPS
2008
15 years 6 months ago
Learning Bounded Treewidth Bayesian Networks
With the increased availability of data for complex domains, it is desirable to learn Bayesian network structures that are sufficiently expressive for generalization while at the ...
Gal Elidan, Stephen Gould
PKDD
2010
Springer
129views Data Mining» more  PKDD 2010»
15 years 2 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
BMCBI
2010
112views more  BMCBI 2010»
15 years 4 months ago
The MetabolomeExpress Project: enabling web-based processing, analysis and transparent dissemination of GC/MS metabolomics datas
Background: Standardization of analytical approaches and reporting methods via community-wide collaboration can work synergistically with web-tool development to result in rapid c...
Adam J. Carroll, Murray R. Badger, A. Harvey Milla...
WWW
2011
ACM
14 years 11 months ago
Parallel boosted regression trees for web search ranking
Gradient Boosted Regression Trees (GBRT) are the current state-of-the-art learning paradigm for machine learned websearch ranking — a domain notorious for very large data sets. ...
Stephen Tyree, Kilian Q. Weinberger, Kunal Agrawal...
BIOINFORMATICS
2005
110views more  BIOINFORMATICS 2005»
15 years 4 months ago
Classification of oligonucleotide fingerprints: application for microbial community and gene expression analyses
Oligonucleotide fingerprinting is an array-based approach used for analysis of microbial community composition and gene expression profiling. Oligonucleotide fingerprinting of rib...
Katechan Jampachaisri, Lea Valinsky, James Bornema...