Wrobel, S. (1996). First Order Theory Refinement. In L. De Raedt (ed.), Advances in Inductive Logic Programming, IOS Press, pp. 14-33  Home/Search Document Details and Download
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On Theory Revision with Queries - Sloan, Turan (1999) (3 citations) (Correct)
....expert can correctly answer membership queries. 1. 1 RELATED WORK Theory revision is one of several problems, also including theory restructuring, which is aimed at making a theory more efficient or transparent, that make up the area of theory refinement in machine learning (see, e.g. Wrobel [28, 29]) There are many systems for theory revision in propositional and predicate logic (e.g. 15, 21, 23, 26] For instance, the EITHER system [21] uses deductive, abductive, and inductive components to revise a propositional Horn theory from a given set of counterexamples. Formal work in theory ....
S. Wrobel. First order theory refinement. In L. De Raedt, editor, Advances in ILP, pages 14--33. IOS Press, Amsterdam, 1995.
More Theory Revision with Queries - Goldsmith, Sloan (2000) (2 citations) (Correct)
....between initial clauses and query clauses is not always one to one. However, the final output of our algorithm is a formula that can be obtained by fixing variables of 0 . 1. 2 Related work In machine learning, there is a large body of work sometimes called theory refinement (see, e.g. Wrobel [22, 23]) Theory refinement includes theory restructuring, which is aimed at making a theory more efficient or transparent, as well as theory revision. Theories are also referred to as knowledge bases, or in computational learning theory as concepts. There are numerous systems for theory revision in ....
S. Wrobel. First order theory refinement. In L. De Raedt, editor, Advances in ILP, pages 14-- 33. IOS Press, Amsterdam, 1995.
A study of two sampling methods for analysing large datasets.. - Srinivasan (1999) (13 citations) (Correct)
....most m examples are chosen randomly from E. 10 ASHWIN SRINIVASAN 3.2. Logical Windowing The development of techniques that revise first order theories is a widely studied research area within Artificial Intelligence. A summary of the issues involved and their relationship to ILP can be found in [39]. Logical windowing constructs theories incrementally by sampling from a large pool of data. During the course of this, it exhibits a rudimentary form of theory revision namely, generalise a set of clauses using the sample data, and specialise them to maintain consistency with the large ....
S. Wrobel. First-order Theory Refinement. In L. De Raedt, editor, Advances in Inductive Logic Programming. IOS Press, Tokyo, 1996.
More Efficient Windowing - Fürnkranz (1997) (Correct)
....the ordering could maliciously effect the performance of the presented algorithms. Additional gains in efficiency could also be achieved by trying to specialize over general rules, instead of entirely removing them. For this purpose we plan to adapt ideas from research in theory revision (Wrobel 1996). Acknowledgements This research is sponsored by the Austrian Fonds zur Forderung der Wissenschaftlichen Forschung (FWF) under grant number P10489 MAT. Financial support for the Austrian Research Institute for Artificial Intelligence is provided by the Austrian Federal Ministry of Science and ....
Wrobel, S. 1996. First order theory refinement. In De Raedt, L., ed., Advances in Inductive Logic Programming.
Applying Theory Revision to the Design of Distributed.. - Baião, Mattoso.. (Correct)
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Wrobel, S. (1996). First Order Theory Refinement. In L. De Raedt (ed.), Advances in Inductive Logic Programming, IOS Press, pp. 14-33
Probabilistic Logic Learning - De Raedt, Kersting (2004) (2 citations) (Correct)
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S. Wrobel. First Order Theory Refinement. In L. De Raedt, editor, Advances in Inductive Logic Programming. IOS Press, 1996.
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