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Abstract: The paper introduces LogAn-H --- a system for learning first-order function-free Horn expressions from interpretations. The system is based on an interactive algorithm (that asks questions) that was proved correct in previous work. The current paper shows how the algorithm can be implemented in a practical system by reducing some ine#ciencies. Moreover, the paper introduces a new algorithm based on it that avoids interaction and learns from examples only. We describe qualitative and... (Update)
Context of citations to this paper: More
.... membership queries (MIS [Sha83] CLINT [RB92] for example) These ideas have also been used in systems that learn from examples only [Kha00]. A learning algorithm for the class of range restricted Horn expressions is presented. The main property of this class is that all the...
.... of theoretical work has shown that larger classes of expressions are learnable if the learner is allowed to ask questions [12, 21, 4, 22, 16, 14, 13, 3, 15]. These works use standard oracles from learning theory [1] as well as new types of questions appropriate for the rst order...
Cited by: More
Learning Recursive Theories in the Normal ILP Setting - Malerba (2003) (Correct)
Learning Closed Horn Expressions - Arias, Khardon (2002) (Correct)
Recent Progress in Learning Horn Expressions with Queries - Khardon (Correct)
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0.3: First-order Cascade ARTMAP - Basilio, Zaverucha, Barbosa (2001) (Correct)
0.3: Ideal Refinement Operators for Theories in the.. - Fanizzi, Ferilli (2002) (Correct)
0.2: Learning Inequated Range Restricted Horn Expressions - Arias, Khardon (2000) (Correct)
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2.0: Learning Horn Expressions with LogAn-H - Khardon (2000) (Correct)
0.1: Learning to Reason with a Restricted View - Khardon, Roth (1998) (Correct)
0.1: Learning to Reason - Khardon (1994) (Correct)
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4: A note on inductive generalization (context) - Plotkin - 1970
3: An overview of the interactive concept learner and theory revisor CLINT (context) - DeRaedt, Bruynooghe - 1992
3: Learning from entailment of logic programs with local variables (context) - Rao, Sattar - 1998
BibTeX entry: (Update)
Roni Khardon. Learning horn expressions with LOGAN-H. To appear in ICML, 2000. http://citeseer.ist.psu.edu/article/khardon00learning.html More
@misc{ khardon00learning,
author = "R. Khardon",
title = "Learning horn expressions with LOGAN-H",
text = "Roni Khardon. Learning horn expressions with LOGAN-H. To appear in ICML,
2000.",
year = "2000",
url = "citeseer.ist.psu.edu/article/khardon00learning.html" }
Citations (may not include all citations):492 Learning logical definitions from relations (context) - Quinlan - 1990
441 Queries and concept learning (context) - Angluin - 1988
328 Algorithmic program debugging (context) - Shapiro - 1983
313 Inductive logic programming: Theory and methods - Muggleton, De Raedt - 1994
130 Inverse entailment and Progol - Muggleton - 1995
69 Top down induction of first order logical decision trees - Blockeel, De Raedt - 1998
65 Structure identification in relational data - Dechter, Pearl - 1992
53 Prolog and naturallanguage analysis (context) - Pereira, Shieber - 1987
51 First order jk-clausal theories are PAC-learnable (context) - De Raedt, Dzeroski - 1994
49 Horn approximations of empirical data - Kautz, Kearns et al. - 1995
30 Inductive constraint logic - De Raedt, Van Laer - 1995
22 Learning function-free Horn expressions - Khardon
20 Learning first order acyclic Horn programs from entailment - Reddy, Tadepalli - 1998
14 Learning from entailment of logic programs with local variab.. (context) - Rao, Sattar - 1998
12 Learning range-restricted Horn expressions - Khardon
3 Refining complete hypotheses in ILP (context) - Bratko - 1999
Documents on the same site (http://www.dcs.ed.ac.uk/home/roni/publications.html): More
Relational Learning for NLP using Linear Threshold Elements - Khardon, Roth (1999) (Correct)
Learning Range Restricted Horn Expressions - Khardon (1999) (Correct)
Reasoning with Models - Khardon, Roth (1996) (Correct)
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