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» The Complexity of Probabilistic EL
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AAAI
2011
12 years 7 months ago
Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...
Chloe Kiddon, Pedro Domingos
CVPR
2008
IEEE
14 years 9 months ago
Sparse probabilistic regression for activity-independent human pose inference
Discriminative approaches to human pose inference involve mapping visual observations to articulated body configurations. Current probabilistic approaches to learn this mapping ha...
Raquel Urtasun, Trevor Darrell
COLT
1994
Springer
13 years 12 months ago
Learning Probabilistic Automata with Variable Memory Length
We propose and analyze a distribution learning algorithm for variable memory length Markov processes. These processes can be described by a subclass of probabilistic nite automata...
Dana Ron, Yoram Singer, Naftali Tishby
ICLP
2010
Springer
13 years 11 months ago
Abductive Inference in Probabilistic Logic Programs
ABSTRACT. Action-probabilistic logic programs (ap-programs) are a class of probabilistic logic programs that have been extensively used during the last few years for modeling behav...
Gerardo I. Simari, V. S. Subrahmanian
AGI
2008
13 years 9 months ago
How Might Probabilistic Reasoning Emerge from the Brain?
: A series of hypotheses is proposed, connecting neural structures and dynamics with the formal structures and processes of probabilistic logic. First, a hypothetical connection is...
Ben Goertzel, Cassio Pennachin