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AI
2002
Springer
13 years 7 months ago
Learning Bayesian networks from data: An information-theory based approach
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
LAMAS
2005
Springer
14 years 28 days ago
An Overview of Cooperative and Competitive Multiagent Learning
Abstract Multi-agent systems (MASs) is an area of distributed artificial intelligence that emphasizes the joint behaviors of agents with some degree of autonomy and the complexiti...
Pieter Jan't Hoen, Karl Tuyls, Liviu Panait, Sean ...
CSFW
2011
IEEE
12 years 7 months ago
Regret Minimizing Audits: A Learning-Theoretic Basis for Privacy Protection
Abstract—Audit mechanisms are essential for privacy protection in permissive access control regimes, such as in hospitals where denying legitimate access requests can adversely a...
Jeremiah Blocki, Nicolas Christin, Anupam Datta, A...
FLAIRS
2004
13 years 8 months ago
Multimodal Function Optimization Using Local Ruggedness Information
In multimodal function optimization, niching techniques create diversification within the population, thus encouraging heterogeneous convergence. The key to the effective diversif...
Jian Zhang 0007, Xiaohui Yuan, Bill P. Buckles
COLT
2003
Springer
14 years 19 days ago
On Learning to Coordinate: Random Bits Help, Insightful Normal Forms, and Competency Isomorphisms
A mere bounded number of random bits judiciously employed by a probabilistically correct algorithmic coordinator is shown to increase the power of learning to coordinate compared ...
John Case, Sanjay Jain, Franco Montagna, Giulia Si...