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» A distributed machine learning framework
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TCBB
2010
176views more  TCBB 2010»
13 years 8 months ago
Feature Selection for Gene Expression Using Model-Based Entropy
—Gene expression data usually contain a large number of genes, but a small number of samples. Feature selection for gene expression data aims at finding a set of genes that best...
Shenghuo Zhu, Dingding Wang, Kai Yu, Tao Li, Yihon...
AAAI
1994
13 years 11 months ago
Solution Reuse in Dynamic Constraint Satisfaction Problems
Many AI problems can be modeled as constraint satisfaction problems (CSP), but many of them are actually dynamic: the set of constraints to consider evolves because of the environ...
Gérard Verfaillie, Thomas Schiex
ICDCS
2009
IEEE
14 years 7 months ago
CLIQUE: Role-Free Clustering with Q-Learning for Wireless Sensor Networks
Clustering and aggregation inherently increase wireless sensor network (WSN) lifetime by collecting information within a cluster at a cluster head, reducing the amount of data thr...
Anna Förster, Amy L. Murphy
JSSPP
2007
Springer
14 years 4 months ago
A Self-optimized Job Scheduler for Heterogeneous Server Clusters
Heterogeneous clusters and grid infrastructures are becoming increasingly popular. In these computing infrastructures, machines have different resources, including memory sizes, d...
Elad Yom-Tov, Yariv Aridor
LOCA
2007
Springer
14 years 4 months ago
Inferring the Everyday Task Capabilities of Locations
Abstract. People rapidly learn the capabilities of a new location, without observing every service and product. Instead they map a few observations to familiar clusters of capabili...
Patricia Shanahan, William G. Griswold