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ILP
2004
Springer
14 years 3 months ago
Macro-Operators Revisited in Inductive Logic Programming
For the last ten years a lot of work has been devoted to propositionalization techniques in relational learning. These techniques change the representation of relational problems t...
Érick Alphonse
AIIA
2003
Springer
14 years 3 months ago
Incremental Induction of Rules for Document Image Understanding
This paper aims at presenting the application of first-order logic machine learning techniques to two document domains in order to learn rules for recognizing the semantic role of...
Stefano Ferilli, Nicola Di Mauro, Teresa Maria Alt...

Publication
352views
14 years 5 months ago
Efficient methods for near-optimal sequential decision making under uncertainty
This chapter discusses decision making under uncertainty. More specifically, it offers an overview of efficient Bayesian and distribution-free algorithms for making near-optimal se...
Christos Dimitrakakis
ECCC
2008
117views more  ECCC 2008»
13 years 10 months ago
The complexity of learning SUBSEQ(A)
Higman essentially showed that if A is any language then SUBSEQ(A) is regular, where SUBSEQ(A) is the language of all subsequences of strings in A. Let s1, s2, s3, . . . be the sta...
Stephen A. Fenner, William I. Gasarch, Brian Posto...
GECCO
2003
Springer
156views Optimization» more  GECCO 2003»
14 years 3 months ago
Facts and Fallacies in Using Genetic Algorithms for Learning Clauses in First-Order Logic
Over the last few years, a few approaches have been proposed aiming to combine genetic and evolutionary computation (GECCO) with inductive logic programming (ILP). The underlying r...
Flaviu Adrian Marginean