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ILP
2007
Springer
13 years 10 months ago
Using Bayesian Networks to Direct Stochastic Search in Inductive Logic Programming
Stochastically searching the space of candidate clauses is an appealing way to scale up ILP to large datasets. We address an approach that uses a Bayesian network model to adaptive...
Louis Oliphant, Jude W. Shavlik
MLG
2007
Springer
13 years 10 months ago
Abductive Stochastic Logic Programs for Metabolic Network Inhibition Learning
Abstract. We revisit an application developed originally using Inductive Logic Programming (ILP) by replacing the underlying Logic Program (LP) description with Stochastic Logic Pr...
Jianzhong Chen, Stephen Muggleton, Jose Santos
ILP
2004
Springer
13 years 10 months ago
Learning an Approximation to Inductive Logic Programming Clause Evaluation
One challenge faced by many Inductive Logic Programming (ILP) systems is poor scalability to problems with large search spaces and many examples. Randomized search methods such as ...
Frank DiMaio, Jude W. Shavlik
NAACL
2001
13 years 5 months ago
Learning Optimal Dialogue Management Rules by Using Reinforcement Learning and Inductive Logic Programming
Developing dialogue systems is a complex process. In particular, designing efficient dialogue management strategies is often difficult as there are no precise guidelines to develo...
Renaud Lecoeuche
AMAI
2008
Springer
13 years 4 months ago
Bayesian learning of Bayesian networks with informative priors
This paper presents and evaluates an approach to Bayesian model averaging where the models are Bayesian nets (BNs). Prior distributions are defined using stochastic logic programs...
Nicos Angelopoulos, James Cussens