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AAAI
2008
15 years 9 months ago
Markov Blanket Feature Selection for Support Vector Machines
Based on Information Theory, optimal feature selection should be carried out by searching Markov blankets. In this paper, we formally analyze the current Markov blanket discovery ...
Jianqiang Shen, Lida Li, Weng-Keen Wong
AAAI
1998
15 years 8 months ago
A* with Bounded Costs
A key assumption of all problem-solving approaches based on utility theory, including heuristic search, is that we can assign a utility or cost to each state. This in turn require...
Brian Logan, Natasha Alechina
UAI
2000
15 years 8 months ago
Exploiting Qualitative Knowledge in the Learning of Conditional Probabilities of Bayesian Networks
Algorithms for learning the conditional probabilities of Bayesian networks with hidden variables typically operate within a high-dimensional search space and yield only locally op...
Frank Wittig, Anthony Jameson
CORR
2010
Springer
157views Education» more  CORR 2010»
15 years 7 months ago
Joint Bandwidth and Power Allocation with Admission Control in Wireless Multi-User Networks With and Without Relaying
Equal allocation of bandwidth and/or power may not be efficient for wireless multi-user networks with limited bandwidth and power resources. Joint bandwidth and power allocation s...
Xiaowen Gong, Sergiy A. Vorobyov, Chintha Tellambu...
ML
2006
ACM
142views Machine Learning» more  ML 2006»
15 years 6 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....