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» A Data Locality Optimizing Algorithm
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ML
2006
ACM
142views Machine Learning» more  ML 2006»
15 years 5 months ago
The max-min hill-climbing Bayesian network structure learning algorithm
We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...
Ioannis Tsamardinos, Laura E. Brown, Constantin F....
INFOCOM
2006
IEEE
15 years 11 months ago
Generalized Proportional Fair Scheduling in Third Generation Wireless Data Networks
—In 3G data networks, network operators would like to balance system throughput while serving users in a fair manner. This is achieved using the notion of proportional fairness. ...
Tian Bu, L. Li, Ramachandran Ramjee
SASO
2009
IEEE
15 years 12 months ago
Self-Organization of Patrolling-Ant Algorithms
—We consider here multi-agent patrolling as the task for a group of agents to repeatedly visit all the cells of a discrete environment. Wagner et al. [1] have introduced patrolli...
Arnaud Glad, Olivier Buffet, Olivier Simonin, Fran...
GECCO
2007
Springer
140views Optimization» more  GECCO 2007»
15 years 11 months ago
Peer-to-peer evolutionary algorithms with adaptive autonomous selection
In this paper we describe and evaluate a fully distributed P2P evolutionary algorithm (EA) with adaptive autonomous selection. Autonomous selection means that decisions regarding ...
W. R. M. U. K. Wickramasinghe, Maarten van Steen, ...
COR
2010
119views more  COR 2010»
15 years 5 months ago
Algorithms for a realistic variant of flowshop scheduling
This paper deals with a realistic variant of flowshop scheduling, namely the hybrid flexible flowshop. A hybrid flowshop mixes the characteristics of regular flowshops and paralle...
B. Naderi, Rubén Ruiz, M. Zandieh