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UAI
1998
14 years 10 months ago
Context-specific approximation in probabilistic inference
There is evidence that the numbers in probabilistic inference don't really matter. This paper considers the idea that we can make a probabilistic model simpler by making fewe...
David Poole
102
Voted
JMLR
2010
192views more  JMLR 2010»
14 years 4 months ago
Inducing Tree-Substitution Grammars
Inducing a grammar from text has proven to be a notoriously challenging learning task despite decades of research. The primary reason for its difficulty is that in order to induce...
Trevor Cohn, Phil Blunsom, Sharon Goldwater
NIPS
1998
14 years 10 months ago
Inference in Multilayer Networks via Large Deviation Bounds
We study probabilistic inference in large, layered Bayesian networks represented as directed acyclic graphs. We show that the intractability of exact inference in such networks do...
Michael J. Kearns, Lawrence K. Saul
110
Voted
IJCAI
1997
14 years 10 months ago
Probabilistic Partial Evaluation: Exploiting Rule Structure in Probabilistic Inference
Bayesian belief networks have grown to prominence because they provide compact representations of many domains, and there are algorithms to exploit this compactness. The next step...
David Poole
59
Voted
IJCAI
2003
14 years 10 months ago
First-order probabilistic inference
Most probabilistic inference algorithms are specified and processed on a propositional level. In the last decade, many proposals for algorithms accepting first-order specificat...
David Poole