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» Learning with Kernels and Logical Representations
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AAAI
2006
14 years 10 days ago
Learning Partially Observable Action Models: Efficient Algorithms
We present tractable, exact algorithms for learning actions' effects and preconditions in partially observable domains. Our algorithms maintain a propositional logical repres...
Dafna Shahaf, Allen Chang, Eyal Amir
SEMWEB
2009
Springer
14 years 5 months ago
An Algorithm for Learning with Probabilistic Description Logics
Probabilistic Description Logics are the basis of ontologies in the Semantic Web. Knowledge representation and reasoning for these logics have been extensively explored in the last...
José Eduardo Ochoa Luna, Fabio Gagliardi Co...
ML
2006
ACM
131views Machine Learning» more  ML 2006»
13 years 11 months ago
Markov logic networks
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge b...
Matthew Richardson, Pedro Domingos
CMSB
2004
Springer
14 years 4 months ago
Modelling Metabolic Pathways Using Stochastic Logic Programs-Based Ensemble Methods
In this paper we present a methodology to estimate rates of enzymatic reactions in metabolic pathways. Our methodology is based on applying stochastic logic learning in ensemble le...
Huma Lodhi, Stephen Muggleton
EMNLP
2007
14 years 11 days ago
Online Learning of Relaxed CCG Grammars for Parsing to Logical Form
We consider the problem of learning to parse sentences to lambda-calculus representations of their underlying semantics and present an algorithm that learns a weighted combinatory...
Luke S. Zettlemoyer, Michael Collins