ILPnet2 library: P.A. Flach

ILP publications by P.A. Flach

This is a list of all publications in the ILPnet2 on-line library which are (co-)authored by P.A. Flach. The title of the article is a link to the full reference, including -- if provided by the author -- abstract and URL. It also allows easy access to related publications.

2003

E. Gyftodimos and P.A. Flach. Hierarchical {B}ayesian Networks: an Approach to Classification and Learning for Structured Data. In T. Horváth and A. Yamamoto, editors, Proceedings of the Work-in-Progress Track at the 13th International Conference on Inductive Logic Programming, pages 12--21. Department of Informatics, University of Szeged, September 2003.
M.-A. Krogel, S. Rawles, F. Zelezný, P.A. Flach, N. Lavrac, and S. Wrobel. Comparative Evaluation of Approaches to Propositionalization. In T. Horváth and A. Yamamoto, editors, Proceedings of the 13th International Conference on Inductive Logic Programming, volume 2835 of Lecture Notes in Artificial Intelligence, pages 197--214. Springer-Verlag, 2003.
D. Mavroeidis and P.A. Flach. Improved Distances for Structured Data. In T. Horváth and A. Yamamoto, editors, Proceedings of the 13th International Conference on Inductive Logic Programming, volume 2835 of Lecture Notes in Artificial Intelligence, pages 251--268. Springer-Verlag, 2003.

2002

T. Gärtner, J. W. Lloyd, and P. A. Flach. Kernels for Structured Data. In S. Matwin and C. Sammut, editors, Proceedings of the 12th International Conference on Inductive Logic Programming, volume 2583 of Lecture Notes in Artificial Intelligence, pages 66--83. Springer-Verlag, 2003.
N. Lachiche and P. A. Flach. 1BC2: a true first-order Bayesian classifier. In S. Matwin and C. Sammut, editors, Proceedings of the 12th International Conference on Inductive Logic Programming, volume 2583 of Lecture Notes in Artificial Intelligence, pages 133--148. Springer-Verlag, 2003.
N. Lavrac, F. Zelezný, and P. A. Flach. RSD: Relational subgroup discovery through first-order feature construction. In S. Matwin and C. Sammut, editors, Proceedings of the 12th International Conference on Inductive Logic Programming, volume 2583 of Lecture Notes in Artificial Intelligence, pages 149--165. Springer-Verlag, 2003.
Peter Flach and Nada Lavrac. Learning in Clausal Logic: A Perspective on Inductive Logic Programming. In Antonis C. Kakas and Fariba Sadri, editors, Computational Logic: Logic Programming and Beyond (Essays in Honour of Robert A. Kowalski), volume 2407 of Lecture Notes in Artificial Intelligence, pages 437--471. Springer-Verlag, Berlin, 2002.

2001

Nada Lavrac and Peter A. Flach. An extended transformation approach to inductive logic programming. ACM Transactions on Computational Logic, 2(4):458--494, October 2001. More behind this link.
Stefan Kramer, Nada Lavrac, and Peter Flach. Propositionalization Approaches to Relational Data Mining. In Saso Dzeroski and Nada Lavrac, editors, Relational Data Mining, pages 262--291. Springer-Verlag, September 2001. More behind this link.
Ljupco Todorovski, Irene Weber, Nada Lavrac, Olga Stepankova, Saso Dzeroski, Dimitar Kazakov, Darko Zupanic, and Peter Flach. Internet Resources on ILP for KDD. In Saso Dzeroski and Nada Lavrac, editors, Relational Data Mining, pages 375--388. Springer-Verlag, September 2001. More behind this link.
Peter A. Flach. On the state of the art in machine learning: A personal review. Artificial Intelligence, 13(1/2):199--222, September 2001. More behind this link.
Peter Flach and Saso Dzeroski. Editorial: Inductive Logic Programming is Coming of Age. Machine Learning, 43(3):207--209, September 2001.
Peter A. Flach and Dragan Gamberger. Subgroup evaluation and decision support for a direct mailing marketing problem. In Christophe Giraud-Carrier, Nada Lavrac, and Steve Moyle, editors, Integrating Aspects of Data Mining, Decision Support and Meta-Learning, pages 45--56. ECML/PKDD'01 workshop notes, September 2001. More behind this link.
Thomas Gärtner, Shaomin Wu, and Peter A. Flach. Data Mining on the Sisyphus Dataset: Evaluation and Integration of Results. In Christophe Giraud-Carrier, Nada Lavrac, and Steve Moyle, editors, Integrating Aspects of Data Mining, Decision Support and Meta-Learning, pages 69--80. ECML/PKDD'01 workshop notes, September 2001. More behind this link.
Thomas Gaertner and Peter A. Flach. WBC_SVM: Weighted Bayesian Classification based on Support Vector Machines. In Carla E. Brodley and Andrea Pohoreckyj Danyluk, editors, Proceedings of the Eighteenth International Conference on Machine Learning, pages 207--209. Morgan Kaufmann, June 2001.
Peter A. Flach and Nicolas Lachiche. Confirmation-Guided Discovery of First-Order Rules with Tertius. Machine Learning, 42(1/2):61--95, January 2001.

2000

Peter A. Flach. Logical characterisations of inductive learning. In Dov M. Gabbay and Rudolf Kruse, editors, Handbook of defeasible reasoning and uncertainty management systems, Vol. 4: Abductive reasoning and learning, pages 155--196. Kluwer Academic Publishers, October 2000.
Peter A. Flach and Antonis C. Kakas. On the relation between abduction and inductive learning. In Dov M. Gabbay and Rudolf Kruse, editors, Handbook of defeasible reasoning and uncertainty management systems, Vol. 4: Abductive reasoning and learning, pages 1--33. Kluwer Academic Publishers, October 2000.
Peter A. Flach. The use of functional and logic languages in machine learning. In Maria Alpuente, editor, Ninth International Workshop on Functional and Logic Programming (WFLP2000), pages 225--237. Universidad Politecnica de Valencia, September 2000. Invited talk More behind this link.
Nicolas Lachiche and Peter Flach. A First-order Representation for Knowledge Discovery and Bayesian Classification on Relational Data. In Pavel Brazdil and Alipio Jorge, editors, PKDD2000 workshop on Data Mining, Decision Support, Meta-learning and ILP : Forum for Practical Problem Presentation and Prospective Solutions, pages 49--60. 4th International Conference on Principles of Data Mining and Knowledge Discovery, September 2000. More behind this link.
Ljupco Todorovski, Peter Flach, and Nada Lavrac. Predictive Performance of Weighted Relative Accuracy. In Djamel A. Zighed, Jan Komorowski, and Jan Zytkow, editors, 4th European Conference on Principles of Data Mining and Knowledge Discovery (PKDD2000), pages 255--264. Springer-Verlag, September 2000. More behind this link.
Peter Flach and Antonis Kakas. The cycle of abductive and inductive knowledge development. In K. Furukawa, S. Muggleton, D. Michie, and L. De Raedt, editors, Proceedings of the Machine Intelligence 17 workshop, pages 17--24. Keio University, July 2000. More behind this link.
Peter A. Flach and Nada Lavrac. The role of feature construction in inductive rule learning. In Luc De Raedt and Stefan Kramer, editors, Proceedings of the ICML2000 workshop on Attribute-Value and Relational Learning: crossing the boundaries, pages 1--11, Stanford, USA, July 2000. More behind this link.
Peter A. Flach and Nicolas Lachiche. Decomposing probability distributions on structured individuals. In Paula Brito, Joaquim Costa, and Donato Malerba, editors, Proceedings of the ECML2000 workshop on Dealing with Structured Data in Machine Learning and Statistics, pages 33--43, Barcelona, Spain, May 2000. More behind this link.
Peter A. Flach and Antonis C. Kakas, editors. Abduction and Induction: Essays on their relation and integration. Kluwer Academic Publishers, April 2000. More behind this link.
Nada Lavrac and Peter Flach. An extended transformation approach to Inductive Logic Programming. Technical Report CSTR-00-002, Department of Computer Science, University of Bristol, March 2000. More behind this link.
Ljupco Todorovski, Peter Flach, and Nada Lavrac. A report on experiments with weighted relative accuracy in CN2. Technical Report CSTR-00-003, Department of Computer Science, University of Bristol, March 2000. More behind this link.
Peter A. Flach and Nicolas Lachiche. Decomposing Probability Distributions on Structured Individuals. In J. Cussens and A. Frisch, editors, Proceedings of the Work-in-Progress Track at the 10th International Conference on Inductive Logic Programming, pages 96--106, 2000. More behind this link.
Iztok Savnik and Peter A. Flach. Discovery of multivalued dependencies from relations. Intelligent Data Analysis, 4(3,4):195--211, 2000.

1999

Peter A. Flach and Iztok Savnik. Database dependency discovery: a machine learning approach. AI Communications, 12(3):139--160, November 1999. More behind this link.
Peter A. Flach. Knowledge representation for inductive learning. In Anthony Hunter and Simon Parsons, editors, Symbolic and Quantitative Approaches to Reasoning and Uncertainty (ECSQARU'99), volume 1638 of Lecture Notes in Artificial Intelligence, pages 160--167. Springer-Verlag, July 1999. More behind this link.
P. Flach and N. Lachiche. 1BC: A First-Order Bayesian Classifier. In S. Dzeroski and P. Flach, editors, Proceedings of the 9th International Workshop on Inductive Logic Programming, volume 1634 of Lecture Notes in Artificial Intelligence, pages 92--103. Springer-Verlag, 1999. More behind this link.
N. Lavrac, P. Flach, and B. Zupan. Rule Evaluation Measures: A Unifying View. In S. Dzeroski and P. Flach, editors, Proceedings of the 9th International Workshop on Inductive Logic Programming, volume 1634 of Lecture Notes in Artificial Intelligence, pages 174--185. Springer-Verlag, 1999.

1998

P.A. Flach, C. Giraud-Carrier, and J.W. Lloyd. Strongly Typed Inductive Concept Learning. In D. Page, editor, Proceedings of the 8th International Conference on Inductive Logic Programming, volume 1446 of Lecture Notes in Artificial Intelligence, pages 185--194. Springer-Verlag, 1998. More behind this link.
P.A. Flach. The logic of learning: a brief introduction to Inductive Logic Programming. In Proceedings of the CompulogNet Area Meeting on Computational Logic and Machine Learning, pages 1--17. University of Manchester, 1998.
P.A. Flach and A.C. Kakas. Abduction and Induction in AI: Report of the IJCAI'97 workshop. Logic Journal of the Interest Group on Pure and Applied Logic, 6(4):651--656, 1998. More behind this link.
P.A. Flach. Comparing consequence relations. In Principles of Knowledge Representation and Reasoning: Proceedings of the Sixth International Conference (KR'98), pages 180--189. Morgan Kaufmann, 1998.
P.A. Flach. From extensional to intensional knowledge: Inductive Logic Programming techniques and their application to deductive databases. In B. Freitag, H. Decker, M. Kifer, and A. Voronkov, editors, Transactions and Change in Logic Databases, volume 1472 of Lecture Notes in Computer Science, pages 356--387. Springer-Verlag, 1998. More behind this link.

1997

P.A. Flach. Normal Forms for Inductive Logic Programming. In S. Dzeroski and N. Lavrac, editors, Proceedings of the 7th International Workshop on Inductive Logic Programming, volume 1297 of Lecture Notes in Artificial Intelligence, pages 149--156. Springer-Verlag, 1997.
P.A. Flach and A.C. Kakas. Abductive and inductive reasoning: report of the ECAI'96 workshop. Logic Journal of the Interest Group on Pure and Applied Logic, 5(5):773--778, 1997. More behind this link.
P.A. Flach and A.C. Kakas. Proceedings of the IJCAI'97 workshop on Abduction and Induction in AI. Technical Report CSTR-97-004, Department of Computer Science, University of Bristol, 1997. More behind this link.
P.A. Flach and N. Lachiche. Cooking up integrity constraints with PRIMUS (preliminary report). Technical Report CSTR-97-009, Department of Computer Science, University of Bristol, 1997. More behind this link.
P.A. Flach and N. Lavrac. Proceedings of the CompulogNet Area Meeting on Representation issues in reasoning and learning. Technical Report CSTR-97-005, Department of Computer Science, University of Bristol, 1997. More behind this link.

1996

P.A. Flach. Rationality postulates for induction. In Y. Shoham, editor, Proceedings of the 6th Conference on Theoretical Aspects of Rationality and Knowledge, pages 267--281. Morgan Kaufmann, 1996.
P.A. Flach. Abduction and induction: inferential and syllogistic perspectives. In P.A. Flach and A. Kakas, editors, Proceedings of the ECAI-96 Workshop on Abductive and Inductive Reasoning, pages 31--35, 1996.

1995

P.A. Flach. Conjectures: An Inquiry Concerning the Logic of Induction. PhD thesis, Katholieke Universiteit Brabant, 1995. More behind this link.

1994

P.A. Flach. Inductive Logic Programming and Philosophy of Science. In S. Wrobel, editor, Proceedings of the 4th International Workshop on Inductive Logic Programming, volume 237 of GMD-Studien, pages 71--84. Gesellschaft für Mathematik und Datenverarbeitung MBH, 1994.
P.A. Flach. Simply Logical: Intelligent Reasoning by Example. John Wiley, 1994. More behind this link.
P.A. Flach. A model of inductive reasoning. In M. Masuch and L. Polos, editors, Knowledge Representation and Reasoning under Uncertainty, volume 808 of Lecture Notes in Artificial Intelligence, pages 41--56. Springer-Verlag, 1994.

1993

P.A. Flach. Predicate Invention in Inductive Data Engineering. In P. Brazdil, editor, Proceedings of the 6th European Conference on Machine Learning, volume 667 of Lecture Notes in Artificial Intelligence, pages 83--94. Springer-Verlag, 1993.
I. Savnik and P.A. Flach. Bottom-up induction of functional dependencies from relations. In G. Piatetsky-Shapiro, editor, Proceedings of the AAAI-93 Workshop on Knowledge Discovery in Databases, pages 174--185, 1993.

1992

P.A. Flach. Generality revisited. In C. Rouveirol, editor, Proceedings of the ECAI-92 Workshop on Logical Approaches to Machine Learning, 1992.
P.A. Flach. A Framework for Inductive Logic Programming. In S. Muggleton, editor, Inductive Logic Programming, pages 193--212. Academic Press, 1992.
P.A. Flach. Logical approaches to machine learning - An overview. THINK, 1(2):25--36, 1992.
P.A. Flach. An analysis of various forms of `jumping to conclusions'. In K. Jantke, editor, Proceedings 3rd International Workshop on Analogical and Inductive Inference, volume 642 of Lecture Notes in Artificial Intelligence, pages 170--186. Springer-Verlag, 1992.

1991

P.A. Flach. Towards a Logical Theory of Inductive Learning. In S. Muggleton, editor, Proceedings of the 1st International Workshop on Inductive Logic Programming, pages 23--32, 1991.
P.A. Flach. Towards a theory of Inductive Logic Programming. In Z.W. Raś and M. Zemankowa, editors, Proceedings of the 5th International Symposium on Methodologies for Intelligent Systems, volume 542 of Lecture Notes in Artificial Intelligence, pages 510--519. Springer-Verlag, 1991.
S-H. Nienhuys-Cheng and P.A. Flach. Consistent Term Mappings, Term Partitions and Inverse Resolution. In Y. Kodratoff, editor, Proceedings of the 5th European Working Session on Learning, volume 482 of Lecture Notes in Artificial Intelligence, pages 361--374. Springer-Verlag, 1991.

1990

P.A. Flach. Inductive characterisation of database relations. In Z.W. Raś, M. Zemankova, and M.L. Emrich, editors, Proceedings of the 4th International Symposium on Methodologies for Intelligent Systems, volume 5, pages 371--378. North-Holland, 1990.