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» The Computational Complexity of Probabilistic Planning
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IJPRAI
2000
83views more  IJPRAI 2000»
13 years 8 months ago
Practical Issues in Modeling Large Diagnostic Systems with Multiply Sectioned Bayesian Networks
As Bayesian networks become widely accepted as a normative formalism for diagnosis based on probabilistic knowledge, they are applied to increasingly larger problem domains. These...
Yanping Xiang, Kristian G. Olesen, Finn Verner Jen...
ICASSP
2011
IEEE
13 years 20 days ago
Outlier-aware robust clustering
Clustering is a basic task in a variety of machine learning applications. Partitioning a set of input vectors into compact, wellseparated subsets can be severely affected by the p...
Pedro A. Forero, Vassilis Kekatos, Georgios B. Gia...
ICC
2011
IEEE
272views Communications» more  ICC 2011»
12 years 8 months ago
Dynamic Anycast Routing and Wavelength Assignment in WDM Networks Using Ant Colony Optimization (ACO)
—Ant colony optimization (ACO) is a probabilistic technique used for solving complex computational problems, such as finding optimal routes in networks. It has been proved to pe...
Kavitha Bhaskaran, Joan Triay, Vinod Vokkarane
ACSC
2008
IEEE
14 years 3 months ago
Privacy preserving set intersection based on bilinear groups
We propose a more efficient privacy preserving set intersection protocol which improves the previously known result by a factor of O(N) in both the computation and communication c...
Yingpeng Sang, Hong Shen
GLOBECOM
2010
IEEE
13 years 7 months ago
Cognitive Network Inference through Bayesian Network Analysis
Cognitive networking deals with applying cognition to the entire network protocol stack for achieving stack-wide as well as network-wide performance goals, unlike cognitive radios ...
Giorgio Quer, Hemanth Meenakshisundaram, Tamma Bhe...