Sciweavers

53 search results - page 6 / 11
» A Logic Programming Framework for Learning by Imitation
Sort
View
ML
2008
ACM
150views Machine Learning» more  ML 2008»
14 years 9 months ago
Learning probabilistic logic models from probabilistic examples
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, José Car...
AIIA
2005
Springer
15 years 3 months ago
Handling Continuous-Valued Attributes in Incremental First-Order Rules Learning
Machine Learning systems are often distinguished according to the kind of representation they use, which can be either propositional or first-order logic. The framework working wi...
Teresa Maria Altomare Basile, Floriana Esposito, N...
CORR
2010
Springer
100views Education» more  CORR 2010»
14 years 9 months ago
Products of Weighted Logic Programs
Abstract. Weighted logic programming, a generalization of bottom-up logic programming, is a successful framework for specifying dynamic programming algorithms. In this setting, pro...
Shay B. Cohen, Robert J. Simmons, Noah A. Smith
ICDAR
2009
IEEE
15 years 4 months ago
Inductive Logic Programming for Symbol Recognition
In this paper, we make an attempt to use Inductive Logic Programming (ILP) to automatically learn non trivial descriptions of symbols, based on a formal description. This work is ...
K. C. Santosh, Bart Lamiroy, Jean-Philippe Ropers
ILP
2007
Springer
15 years 3 months ago
Learning with Kernels and Logical Representations
In this chapter, we describe a view of statistical learning in the inductive logic programming setting based on kernel methods. The relational representation of data and background...
Paolo Frasconi