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» Incremental Probabilistic Inference
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FTML
2008
185views more  FTML 2008»
13 years 10 months ago
Graphical Models, Exponential Families, and Variational Inference
The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building large-scale multivariate stat...
Martin J. Wainwright, Michael I. Jordan
AAAI
2000
13 years 11 months ago
Semantics and Inference for Recursive Probability Models
In recent years, there have been several proposals that extend the expressive power of Bayesian networks with that of relational models. These languages open the possibility for t...
Avi Pfeffer, Daphne Koller
UAI
1993
13 years 11 months ago
Causal Independence for Knowledge Acquisition and Inference
I introduce a temporal belief-network representation of causal independence that a knowledge engineer can use to elicit probabilistic models. Like the current, atemporal belief-ne...
David Heckerman
CVIU
2004
132views more  CVIU 2004»
13 years 9 months ago
Layered representations for learning and inferring office activity from multiple sensory channels
We present the use of layered probabilistic representations for modeling human activities, and describe how we use the representation to do sensing, learning, and inference at mul...
Nuria Oliver, Ashutosh Garg, Eric Horvitz
JMLR
2010
88views more  JMLR 2010»
13 years 4 months ago
Inference and Learning in Networks of Queues
Probabilistic models of the performance of computer systems are useful both for predicting system performance in new conditions, and for diagnosing past performance problems. The ...
Charles A. Sutton, Michael I. Jordan