Registration: First Floor, Building K17, Schoolof Computer Science and Engineering                                                      ILP Technical Program: Main Seminar Room, First Floor, Building K17, School of Computer Science and Engineering





8:45: Welcome and Introductory Remarks: Stan Matwin, U. of Ottawa, Claude Sammut, UNSW


9: 00: Invited Talk:

John Shawe-Taylor

9:00 Invited Talk


COLT /ICML -Christos Papadimitriou

check ICML schedule for location

9:00 Invited Talk


ILP/ICML Saso Dzeroski

check ICML schedule for location

Tea Break

Tea Break

Tea Break

10:30-12:30 Relational Data Mining

Chair: Ivan Bratko, Josef  Stefan Institute

Compact representation of knowledge bases in ILP; Jan Struyf, Jan Ramon,  Hendrik Blockeel, Katholieke Universiteit Leuven,


Experimental Investigaton of Pruning Strategies for Relational Pattern Discovery; Irene Weber, Universität Stuttgart


Mining Frequent Logical Sequences with Spiritlog; Cyrille Masson  INSA Lyon, Francois Jacquenet, Université Saint-Etienne


A Polynomial Time Matching Algorithm of Structured Ordered Tree Patterns for Data Mining from Semistructured Data: Yusuke Suzuki, Kohtaro Inomae,  Takayoshi Shoudai: Kyushu University, Tetsuhiro Miyahara, Tomoyuki Uchida: Hiroshima City University

10:30-12:30 Learning Probabilistic and Statistical Models

Chair: Jorg Uwe Kietz, kdlabs AG

Linkage and Autocorrelation Cause Bias in Accuracy Estimates; David Jensen, Jennifer Neville, University of Massachusetts


Revision of First-Order Bayesian Classifiers; Kate Revoredo,  Gerson Zaverucha, Universidade Federal de Rio de Janeiro


1BC2: a true first-order Bayesian classifier; Nicolas Lachiche, LSIIT - Université Robert Schumann, Peter Flach, University of Bristol


Learning structure and parameters of Stochastic Logic Programs; Stephen Muggleton, Imperial College

10:30-12:00 Implementation issues and comparisons

Chair: Prasad Tadepalli, Oregon State U.

A Genetic Algorithms approach to ILP; Alireza Tamaddoni-Nezhad, Stephen Muggleton, Imperial College London


Efficient and Effective Induction of First Order Decision Lists; Mary Elaine Califf, Illinois State University


Experimental Comparison of Graph-Based Relational Concept Learning with Inductive Logic Programming Systems; Jesus Gonzalez, Instituto Nacional de Astrofisica Optica y Electronica, Lawrence Holder, Diane Cook: University of Texas at Arlington


Lunch Break

Lunch Break

Lunch Break

14:00-15:30 Learnability/ space properties

Chair: Celine Rouveirol, U.  Paris-Sud


The Applicability to ILP of Results Concerning the Ordering of Binomial Populations; Ashwin Srinivasan, Oxford University


Lattice-Search Runtime Distributions May Be Heavy-Tailed; Filip Zelezny, Czech Technical University, Ashwin Srinivasan, Oxford University, David Page, University of Wisconsin


Learnability of Description Logic Programs; Jörg-Uwe Kietz, kdlabs AG,  Zurich

14:00-15:30 Learning in the presence of domain knowledge

Chair: Stepehen Muggleton, Imperial College


Noise-resistant Incremental Relational Learning using Possible Worlds; James Westendorp, The University of New South Wales


Using Theory Completion to learn a Robot Navigation Control Program; Steve Moyle, Oxford University


Genetic Programming with Domain Knowledge for Machine Discovery; Alain Ratle, ISAT, Michele Sebag, Universite Paris Sud


14:00-15:30 Ensemble learning/SVM

Chair: Bernhard Pfahringer, U. of Waikato


Scaling Boosting by Margin-Based Inclusion of Features and Relations; Susanne Hoche, Stefan Wrobel: Otto-von-Guericke-Universität


An Empirical Evaluation of Bagging in Inductive Logic Programming; Ines Dutra, David Page,Vitor Santos Costa, Jude Shavlik: University of Wisconsin


Kernels for Structured Data  Thomas Gaertner, Fraunhofer Institut Autonome Intelligente Systeme, John Lloyd, The Australian National University,  Peter Flach, University of Bristol

Tea Break

Tea Break

Tea Break

16:00-17:30 Work in Progress Session

Chair: Stan Matwin, U of Ottawa


1.E. Alphonse, N. Stroppa, Filtering MIPs as a Method for ILP Dimensionality Reducation

2. L. Badea: Functional Discrimination of Gene Expression Patterns Using ILP

3. V.S. Costa, D. Page: CLP(B)  in School: ILP and Bayesian Networks

4. Dzeroski et al. Relational Ranking with Predictive Clustering Trees

5. E. Gyftodimos, P. Flach, Hierarchical Bayesian Networks

6.J. Heasman, S. Moyle, Learning To Detect Intrusion Strategies

7.Kersting et al. Towards Discovering Structuring Signatures of Protein Folds…

8.T. Konik, J. Laird, Hierarch. Proc. Knowledge Learning Through Observation using ILP

9.R. Otero, Experiments on the Frame Problem in Induction

10.H. Watanabe, S. Muggleton, Towards Learning A First-Order Action Language

16:00-17:30 Propositionalization/clustering

Chair: Stefan Kramer, U. of Freiburg


Learning with Feature Description Logics, Chad Cumby, Dan Roth: University of Illinois at Urbana/Champaign


Propositionalization for Clustering Symbolic Relational Descriptions; Isabelle Bournaud, Université Paris Sud, Mélanie Courtine, Jean-Daniel Zucker, Université Paris 6


RSD: Relational subgroup discovery through first-order feature construction; Nada Lavrac, Institute Josef Stefan, Filip Zelezny, Czech Technical University, Peter Flach, University of Bristol, UK


16:00-17:30 Panel "If I had to start a Ph.D. in ILP today, what would my topic be?"

Panelists:  I. Bratko, (Josef Stefan Institute) P. Flach (U. of Bristol), J. Lloyd (Australian National U.), S. Muggleton (Imerial College), C. Rouveirol (U. Paris-Sud), P. Tadepalli (Oregon State U.)





17:30-18:15 Community meeting

Reception 18:00-21:00, Scientia Foyer

Banquet 18:30

Reception and ICML poster session, 18:30-20:30  Square House