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Volumn 6, Issue , 2005, Pages 1919-1938

New Horn revision algorithms

Author keywords

Computational learning theory; Exact learning; Horn formulas; Query learning; Theory revision

Indexed keywords

COMPUTATIONAL LEARNING THEORY; HORN FORMULAS; THEORY REVISION;

EID: 29144523152     PISSN: 15337928     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (7)

References (29)
  • 1
    • 0003837807 scopus 로고
    • Learning propositional Horn sentences with hints
    • Department of Computer Science, Yale University, December
    • Dana Angluin. Learning propositional Horn sentences with hints. Technical Report YALEU/DCS/RR-590, Department of Computer Science, Yale University, December 1987a.
    • (1987) Technical Report , vol.YALEU-DCS-RR-590
    • Angluin, D.1
  • 2
    • 0023453626 scopus 로고
    • Learning regular sets from queries and counterexamples
    • November
    • Dana Angluin. Learning regular sets from queries and counterexamples. Inform. Comput., 75(2):87-106, November 1987b.
    • (1987) Inform. Comput. , vol.75 , Issue.2 , pp. 87-106
    • Angluin, D.1
  • 3
    • 0000710299 scopus 로고
    • Queries and concept learning
    • April
    • Dana Angluin. Queries and concept learning. Machine Learning, 2(4):319-342, April 1988.
    • (1988) Machine Learning , vol.2 , Issue.4 , pp. 319-342
    • Angluin, D.1
  • 4
    • 0000452640 scopus 로고
    • Learning conjunctions of Horn clauses
    • Dana Angluin, Michael Frazier, and Leonard Pitt. Learning conjunctions of Horn clauses. Machine Learning, 9:147-164, 1992.
    • (1992) Machine Learning , vol.9 , pp. 147-164
    • Angluin, D.1    Frazier, M.2    Pitt, L.3
  • 5
    • 0002198395 scopus 로고
    • Towards a theory of declarative knowledge
    • J. Minker, editor. Morgan Kaufmann, Los Altos, CA
    • Krzysztof R. Apt, Howard Blair, and Adrian Walker. Towards a theory of declarative knowledge. In J. Minker, editor, Foundations of Deductive Databases and Logic Programming, pages 193-216. Morgan Kaufmann, Los Altos, CA, 1988.
    • (1988) Foundations of Deductive Databases and Logic Programming , pp. 193-216
    • Apt, K.R.1    Blair, H.2    Walker, A.3
  • 6
    • 84958061126 scopus 로고    scopus 로고
    • Learning acyclic first-order Horn sentences from entailment
    • Algorithmic Learning Theory, 8th International Workshop, ALT '97, Sendai, Japan, October 1997, Proceedings. Springer
    • Hiroki Arimura. Learning acyclic first-order Horn sentences from entailment. In Algorithmic Learning Theory, 8th International Workshop, ALT '97, Sendai, Japan, October 1997, Proceedings, volume 1316 of Lecture Notes in Artificial Intelligence, pages 432-445. Springer, 1997.
    • (1997) Lecture Notes in Artificial Intelligence , vol.1316 , pp. 432-445
    • Arimura, H.1
  • 7
    • 0032595785 scopus 로고    scopus 로고
    • Structural results about on-line learning models with and without queries
    • Peter Auer and Philip M. Long. Structural results about on-line learning models with and without queries. Machine Learning, 36(3):147-181, 1999.
    • (1999) Machine Learning , vol.36 , Issue.3 , pp. 147-181
    • Auer, P.1    Long, P.M.2
  • 8
    • 0029254047 scopus 로고
    • Learning in the presence of finitely or infinitely many irrelevant attributes
    • Earlier version in 4th COLT, 1991
    • Avrim Blum, Lisa Hellerstein, and Nick Littlestone. Learning in the presence of finitely or infinitely many irrelevant attributes. J. of Comput. Syst. Sci., 50(1):32-40, 1995. Earlier version in 4th COLT, 1991.
    • (1995) J. of Comput. Syst. Sci. , vol.50 , Issue.1 , pp. 32-40
    • Blum, A.1    Hellerstein, L.2    Littlestone, N.3
  • 10
    • 58149319164 scopus 로고
    • Exact learning Boolean function via the monotone theory
    • Nader Bshouty. Exact learning Boolean function via the monotone theory. Information and Computation, 123:146-153, 1995.
    • (1995) Information and Computation , vol.123 , pp. 146-153
    • Bshouty, N.1
  • 11
    • 0032090599 scopus 로고    scopus 로고
    • Attribute-efficient learning in query and mistake-bound models
    • Nader Bshouty and Lisa Hellerstein. Attribute-efficient learning in query and mistake-bound models. J. of Comput. Syst. Sci., 56(3):310-319, 1998.
    • (1998) J. of Comput. Syst. Sci. , vol.56 , Issue.3 , pp. 310-319
    • Bshouty, N.1    Hellerstein, L.2
  • 13
    • 22944462563 scopus 로고    scopus 로고
    • Master's thesis, Dept. of Computer Science, University of Kentucky
    • Jignesh Umesh Doshi. Revising Horn formulas. Master's thesis, Dept. of Computer Science, University of Kentucky, 2003.
    • (2003) Revising Horn Formulas
    • Doshi, J.U.1
  • 14
    • 0036568019 scopus 로고    scopus 로고
    • Theory revision with queries: DNF formulas
    • Judy Goldsmith, Robert H. Sloan, and György Turán. Theory revision with queries: DNF formulas. Machine Learning, 47(2/3):257-295, 2002.
    • (2002) Machine Learning , vol.47 , Issue.2-3 , pp. 257-295
    • Goldsmith, J.1    Sloan, R.H.2    Turán, G.3
  • 15
    • 22944434553 scopus 로고    scopus 로고
    • New revision algorithms
    • Algorithmic Learning Theory, 15th International Conference, ALT 2004, Padova, Italy, October 2004, Proceedings. Springer
    • Judy Goldsmith, Robert H. Sloan, Balázs Szörényi, and György Turán. New revision algorithms. In Algorithmic Learning Theory, 15th International Conference, ALT 2004, Padova, Italy, October 2004, Proceedings, volume 3244 of Lecture Notes in Artificial Intelligence, pages 395-409. Springer, 2004a.
    • (2004) Lecture Notes in Artificial Intelligence , vol.3244 , pp. 395-409
    • Goldsmith, J.1    Sloan, R.H.2    Szörényi, B.3    Turán, G.4
  • 16
    • 2442715513 scopus 로고    scopus 로고
    • Theory revision with queries: Horn, read-once, and parity formulas
    • Judy Goldsmith, Robert H. Sloan, Balázs Szörényi, and György Turán. Theory revision with queries: Horn, read-once, and parity formulas. Artificial Intelligence, 156:139-176, 2004b.
    • (2004) Artificial Intelligence , vol.156 , pp. 139-176
    • Goldsmith, J.1    Sloan, R.H.2    Szörényi, B.3    Turán, G.4
  • 17
    • 0033076455 scopus 로고    scopus 로고
    • The complexity of theory revision
    • Russell Greiner. The complexity of theory revision. Artificial Intelligence, 107:175-217, 1999a.
    • (1999) Artificial Intelligence , vol.107 , pp. 175-217
    • Greiner, R.1
  • 18
    • 0032635970 scopus 로고    scopus 로고
    • The complexity of revising logic programs
    • Russell Greiner. The complexity of revising logic programs. J. Logic Programming, 40:273-298, 1999b.
    • (1999) J. Logic Programming , vol.40 , pp. 273-298
    • Greiner, R.1
  • 19
    • 0029390560 scopus 로고
    • Quasi-acyclic propositional Horn knowledge bases: Optimal compression
    • Peter L. Hammer and Alexander Kogan. Quasi-acyclic propositional Horn knowledge bases: optimal compression. IEEE Trans. Knowl. Data Eng., 7:751-762, 1995.
    • (1995) IEEE Trans. Knowl. Data Eng. , vol.7 , pp. 751-762
    • Hammer, P.L.1    Kogan, A.2
  • 21
  • 22
    • 0008242869 scopus 로고
    • A preliminary PAC analysis of theory revision
    • Thomas Petsche, editor, Selecting Good Models, chapter 3. MIT Press
    • Raymond J. Mooney. A preliminary PAC analysis of theory revision. In Thomas Petsche, editor, Computational Learning Theory and Natural Learning Systems, volume III: Selecting Good Models, chapter 3, pages 43-53. MIT Press, 1995.
    • (1995) Computational Learning Theory and Natural Learning Systems , vol.3 , pp. 43-53
    • Mooney, R.J.1
  • 23
    • 0028407918 scopus 로고
    • Theory refinement combining analytical and empirical methods
    • Dirk Ourston and Raymond J. Mooney. Theory refinement combining analytical and empirical methods. Artificial Intelligence, 66:273-309, 1994.
    • (1994) Artificial Intelligence , vol.66 , pp. 273-309
    • Ourston, D.1    Mooney, R.J.2
  • 24
    • 0029308579 scopus 로고
    • Automated refinement of first-order Horn-clause domain theories
    • Bradley L. Richards and Raymond J. Mooney. Automated refinement of first-order Horn-clause domain theories. Machine Learning, 19:95-131, 1995.
    • (1995) Machine Learning , vol.19 , pp. 95-131
    • Richards, B.L.1    Mooney, R.J.2
  • 25
    • 2442699209 scopus 로고    scopus 로고
    • Projective DNF formulae and their revision
    • Learning Theory and Kernel Machines, 16th Annual Conference on Learning Theory and 7th Kernel Workshop, COLT/Kernel 2003, Washington, DC, USA, August 24-27, 2003, Proceedings. Springer
    • Robert H. Sloan, Balázs Szörényi, and György Turán. Projective DNF formulae and their revision. In Learning Theory and Kernel Machines, 16th Annual Conference on Learning Theory and 7th Kernel Workshop, COLT/Kernel 2003, Washington, DC, USA, August 24-27, 2003, Proceedings, volume 2777 of Lecture Notes in Artificial Intelligence, pages 625-639. Springer, 2003.
    • (2003) Lecture Notes in Artificial Intelligence , vol.2777 , pp. 625-639
    • Sloan, R.H.1    Szörényi, B.2    Turán, G.3
  • 26
    • 0027678679 scopus 로고
    • Extracting refined rules from knowledge-based neural networks
    • Geoffrey G. Towell and Jude W. Shavlik. Extracting refined rules from knowledge-based neural networks. Machine Learning, 13:71-101, 1993.
    • (1993) Machine Learning , vol.13 , pp. 71-101
    • Towell, G.G.1    Shavlik, J.W.2
  • 27
    • 0009134962 scopus 로고
    • Negation as failure using tight derivations for general logic programs
    • J. Minker, editor. Morgan Kaufmann, Los Altos, CA
    • Allen Van Gelder. Negation as failure using tight derivations for general logic programs. In J. Minker, editor, Foundations of Deductive Databases and Logic Programming, pages 149-176. Morgan Kaufmann, Los Altos, CA, 1988.
    • (1988) Foundations of Deductive Databases and Logic Programming , pp. 149-176
    • Van Gelder, A.1
  • 28
    • 0001936070 scopus 로고
    • First order theory refinement
    • L. De Raedt, editor. IOS Press, Amsterdam
    • Stefan Wrobel. First order theory refinement. In L. De Raedt, editor, Advances in ILP, pages 14-33. IOS Press, Amsterdam, 1995.
    • (1995) Advances in ILP , pp. 14-33
    • Wrobel, S.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.