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EXPERT
1998
83views more  EXPERT 1998»
13 years 6 months ago
Data-Driven Constructive Induction
Constructive induction divides the problem of learning an inductive hypothesis into two intertwined searches: one—for the “best” representation space, and two—for the “be...
Eric Bloedorn, Ryszard S. Michalski
ILP
2004
Springer
13 years 11 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
JMLR
2012
11 years 8 months ago
UPAL: Unbiased Pool Based Active Learning
In this paper we address the problem of pool based active learning, and provide an algorithm, called UPAL, that works by minimizing the unbiased estimator of the risk of a hypothe...
Ravi Ganti, Alexander Gray
ML
2008
ACM
13 years 6 months ago
Large margin vs. large volume in transductive learning
Abstract. We consider a large volume principle for transductive learning that prioritizes the transductive equivalence classes according to the volume they occupy in hypothesis spa...
Ran El-Yaniv, Dmitry Pechyony, Vladimir Vapnik
COR
2010
146views more  COR 2010»
13 years 6 months ago
A search space "cartography" for guiding graph coloring heuristics
We present a search space analysis and its application in improving local search algorithms for the graph coloring problem. Using a classical distance measure between colorings, w...
Daniel Cosmin Porumbel, Jin-Kao Hao, Pascale Kuntz