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» Decision Making Using Probabilistic Inference Methods
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STOC
1997
ACM
97views Algorithms» more  STOC 1997»
15 years 6 months ago
Using and Combining Predictors That Specialize
Abstract. We study online learning algorithms that predict by combining the predictions of several subordinate prediction algorithms, sometimes called “experts.” These simple a...
Yoav Freund, Robert E. Schapire, Yoram Singer, Man...
INFOCOM
2006
IEEE
15 years 8 months ago
Establishing Pair-Wise Keys in Heterogeneous Sensor Networks
— Many applications that make use of sensor networks require secure communication. Because asymmetric-key solutions are difficult to implement in such a resource-constrained env...
Patrick Traynor, Heesook Choi, Guohong Cao, Sencun...
UAI
2003
15 years 3 months ago
The Information Bottleneck EM Algorithm
Learning with hidden variables is a central challenge in probabilistic graphical models that has important implications for many real-life problems. The classical approach is usin...
Gal Elidan, Nir Friedman
ICCV
2007
IEEE
16 years 4 months ago
Graph-Cut Transducers for Relevance Feedback in Content Based Image Retrieval
Closing the semantic gap in content based image retrieval (CBIR) basically requires the knowledge of the user's intention which is usually translated into a sequence of quest...
Hichem Sahbi, Jean-Yves Audibert, Renaud Keriven
111
Voted
KDD
2002
ACM
127views Data Mining» more  KDD 2002»
16 years 2 months ago
Mining knowledge-sharing sites for viral marketing
Viral marketing takes advantage of networks of influence among customers to inexpensively achieve large changes in behavior. Our research seeks to put it on a firmer footing by mi...
Matthew Richardson, Pedro Domingos