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» Tractable Inference for Complex Stochastic Processes
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NIPS
2000
13 years 8 months ago
Learning Joint Statistical Models for Audio-Visual Fusion and Segregation
People can understand complex auditory and visual information, often using one to disambiguate the other. Automated analysis, even at a lowlevel, faces severe challenges, includin...
John W. Fisher III, Trevor Darrell, William T. Fre...
ICDE
2009
IEEE
178views Database» more  ICDE 2009»
13 years 5 months ago
Efficient Query Evaluation over Temporally Correlated Probabilistic Streams
Many real world applications such as sensor networks and other monitoring applications naturally generate probabilistic streams that are highly correlated in both time and space. ...
Bhargav Kanagal, Amol Deshpande
JAIR
2008
145views more  JAIR 2008»
13 years 7 months ago
Communication-Based Decomposition Mechanisms for Decentralized MDPs
Multi-agent planning in stochastic environments can be framed formally as a decentralized Markov decision problem. Many real-life distributed problems that arise in manufacturing,...
Claudia V. Goldman, Shlomo Zilberstein
ICML
2004
IEEE
14 years 8 months ago
Learning associative Markov networks
Markov networks are extensively used to model complex sequential, spatial, and relational interactions in fields as diverse as image processing, natural language analysis, and bio...
Benjamin Taskar, Vassil Chatalbashev, Daphne Kolle...
PODS
2008
ACM
123views Database» more  PODS 2008»
14 years 7 months ago
Evaluating rank joins with optimal cost
In the rank join problem, we are given a set of relations and a scoring function, and the goal is to return the join results with the top K scores. It is often the case in practic...
Karl Schnaitter, Neoklis Polyzotis