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» A distributed machine learning framework
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TCBB
2010
176views more  TCBB 2010»
14 years 11 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
15 years 2 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
99
Voted
ICDCS
2009
IEEE
15 years 10 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
106
Voted
JSSPP
2007
Springer
15 years 7 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
15 years 7 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