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ICASSP
2009
IEEE
16 years 19 days ago
Structured variational methods for distributed inference in wireless ad hoc and sensor networks
Abstract –In this paper, a variational message passing framework is proposed for Markov random fields, which is computationally more efficient and admits wider applicability comp...
Yanbing Zhang, Huaiyu Dai
SEMWEB
2007
Springer
16 years 15 hour ago
Using the Dempster-Shafer Theory of Evidence to Resolve ABox Inconsistencies
Abstract. Automated ontology population using information extraction algorithms can produce inconsistent knowledge bases. Confidence values assigned by the extraction algorithms m...
Andriy Nikolov, Victoria S. Uren, Enrico Motta, An...
TIT
2008
87views more  TIT 2008»
15 years 4 months ago
Maxwell Construction: The Hidden Bridge Between Iterative and Maximum a Posteriori Decoding
There is a fundamental relationship between belief propagation and maximum a posteriori decoding. A decoding algorithm, which we call the Maxwell decoder, is introduced and provide...
Cyril Measson, Andrea Montanari, Rüdiger L. U...
CHI
2011
ACM
14 years 9 months ago
Apolo: making sense of large network data by combining rich user interaction and machine learning
Extracting useful knowledge from large network datasets has become a fundamental challenge in many domains, from scientific literature to social networks and the web. We introduc...
Duen Horng Chau, Aniket Kittur, Jason I. Hong, Chr...
CORR
2012
Springer
170views Education» more  CORR 2012»
14 years 1 months ago
What Cannot be Learned with Bethe Approximations
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
Uri Heinemann, Amir Globerson