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» Complexity of Inference in Graphical Models
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AAAI
2012
11 years 10 months ago
A Tractable First-Order Probabilistic Logic
Tractable subsets of first-order logic are a central topic in AI research. Several of these formalisms have been used as the basis for first-order probabilistic languages. Howev...
Pedro Domingos, William Austin Webb
ICFP
2008
ACM
14 years 7 months ago
From ML to MLF: graphic type constraints with efficient type inference
MLF is a type system that seamlessly merges ML-style type inference with System-F polymorphism. We propose a system of graphic (type) constraints that can be used to perform type ...
Boris Yakobowski, Didier Rémy
JMLR
2012
11 years 10 months ago
Low rank continuous-space graphical models
Constructing tractable dependent probability distributions over structured continuous random vectors is a central problem in statistics and machine learning. It has proven diffic...
Carl Smith, Frank Wood, Liam Paninski
AAAI
2010
13 years 9 months ago
Efficient Lifting for Online Probabilistic Inference
Lifting can greatly reduce the cost of inference on firstorder probabilistic graphical models, but constructing the lifted network can itself be quite costly. In online applicatio...
Aniruddh Nath, Pedro Domingos