Thomas Gärtner

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25.11.2009 KDML co-organizes AAAI-10 Workshop on Statistical Relational AI (StarAI) 02.11.2009 KDML collaborates with theme park "Phantasialand" 22.10.2009 Dr. Thomas Gärtner received an Emmy Noether Fellowship more news...

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Thomas Gärtner

	Leading Research on Computational Aspects of Mining and Learning
	Fraunhofer IAIS
	Knowledge Discovery
	Tel.: +49 2241 14 3513 E-Mail: thomas.gaertner iais.fraunhofer.de
	my homepage in here and my much much older but still existing one in Bristol
	Schloss Birlinghoven 53757 Sankt Augustin

My main research interest is on machine learning. So far I focussed mainly on kernel methods and learning with graphs. Recently, I am also developing interests in transductive and semi-supervised learning.

"Our critics are our friends, because they show us our faults." - Benjamin Franklin
"Even if you're on the right track, you'll get run over if you just sit there" - Will Rogers

[ Overview | Publications | Activities | Research Interests ]

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Publications

Some selected publications are listed below. I am still trying to keep this up to date, though you should also look [@DBLP], [@springer], [@scholär], [@scholaer], or [@acm].

Thomas Gärtner, Shankar Vembu. On Structured Output Training: Hard Cases and an Efficient Alternative. Machine Learning Journal (Special Issue of ECML PKDD), 76(2):227–242, 2009. [ preprint | BibTeX ]
Hanna Geppert, Jens Humrich, Dagmar Stumpfe, Thomas Gärtner, Jürgen Bajorath. Ligand Prediction from Protein Sequence and Small Molecule Information Using Support Vector Machines and Fingerprint Descriptors. Journal of Chemical Information and Modeling, 49(4):767-779, 2009. [ BibTeX ]
Shankar Vembu, Thomas Gärtner, Mario Boley. Probabilistic Structured Predictors. Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence (UAI), 2009. [ pdf | slides | BibTeX ]
Olana Missura, Thomas Gärtner. Online Adaptive Agent for Connect Four. Proceedings of the Fourth International Conference on Games Research and Development CyberGames 2008, page 1-8. 2008. [ pdf | BibTeX ]
Hanna Geppert, Tamás Horváth, Thomas Gärtner, Stefan Wrobel, Jürgen Bajorath. Support-Vector-Machine-Based Ranking Significantly Improves the Effectiveness of Similarity Searching Using 2D Fingerprints and Multiple Reference Compounds. Journal of Chemical Information and Modeling, 2008. [ BibTeX ]
K. Zapien, T. Gärtner, G. Gasso, S. Canu. Regularization path for ranking svm. Proceedings of the 11th European Symposium on Artificial Neural Networks, April 2008. [ BibTeX ]
Thomas Gärtner, Gemma C. Garriga. The Cost of Learning Directed Cuts. Proceedings of the 18th European Conference on Machine Learning, 2007. [ pdf | BibTeX ]
Ulf Brefeld, Thomas Gärtner, Tobias Scheffer, Stefan Wrobel. Efficient Co-Regularised Least Squares Regression. Proceedings of the 23rd International Conference on Machine Learning, 2006. ACM Press. [ @imls | BibTeX ]
Thomas Gärtner, Gemma C. Garriga, Thorsten Meinl, editor(s). Proceedings of The Workshop on Mining and Learning with Graphs. 2006. [ pdf | BibTeX ]
Quoc V. Le, Alex J. Smola, Thomas Gärtner. Simpler Knowledge-based Support Vector Machines. Proceedings of the 23rd International Conference on Machine Learning, 2006. ACM Press. [ @imls | BibTeX ]
Kurt Driessens, Jan Ramon, Thomas Gärtner. Graph Kernels and Gaussian Processes for Relational Reinforcement Learning. Machine Learning, 2006. [ @springer | BibTeX ]
Thomas Gärtner, Quoc V. Le, Simon Burton, Alex J. Smola, S.V.N. Vishwanathan. Large-Scale Multiclass Transduction. Advances in Neural Information Processing Systems 18, 2006. [ @books.nips | BibTeX ]
Quoc V. Le, Alex J. Smola, Thomas Gärtner, Yasemin Altun. Transductive Gaussian Process Regression with Automatic Model Selection. Proceedings of the 17th European Conference on Machine Learning, 2006. Springer-Verlag. [ @springer | BibTeX ]
Thomas Gärtner. Kernels for Structured Data. Universität Bonn, 2005. [ BibTeX ]
Thomas Gärtner, John W. Lloyd, Peter A. Flach. Kernels and Distances for Structured Data. Machine Learning, 2004. [ @springer | BibTeX ]
Tamas Horvath, Thomas Gärtner, Stefan Wrobel. Cyclic Pattern Kernels for Predictive Graph Mining. Proceedings of the International Conference on Knowledge Discovery and Data Mining, 2004. [ @portal.acm | BibTeX ]
Thomas Gärtner, Peter A. Flach, Stefan Wrobel. On Graph Kernels: Hardness Results and Efficient Alternatives. Proceedings of the 16th Annual Conference on Computational Learning Theory and the 7th Kernel Workshop, 2003. [ @springer | BibTeX ]
Thomas Gärtner, Kurt Driessens, Jan Ramon. Graph Kernels and Gaussian Processes for Relational Reinforcement Learning. Proceedings of the 13th International Conference on Inductive Logic Programming, 2003. [ BibTeX ]
Thomas Gärtner. A Survey of Kernels for Structured Data. SIGKDD Explorations, 2003. [ @portal.acm | @sigkdd | BibTeX ]
Thomas Gärtner, Peter A. Flach, Adam Kowalczyk, Alex J. Smola. Multi-Instance Kernels. Proceedings of the 19th International Conference on Machine Learning, 2002. Morgan Kaufmann. [ BibTeX ]
Thomas Gärtner, John W. Lloyd, Peter A. Flach. Kernels for Structured Data. Proceedings of the 12th International Conference on Inductive Logic Programming, 2002. Springer-Verlag. [ BibTeX ]
Thomas Gärtner, Peter A. Flach. WBCsvm: Weighted Bayesian Classification based on Support Vector Machines. Proceedings of the 18th International Conference on Machine Learning, 2001. Morgan Kaufmann. [ BibTeX ]

[ Overview | Publications | Activities | Research Interests ]

Activities

Action Editor since 2009 and Editorial Board Member since 2006 of the Machine Learning Journal ( MLJ )
Workshop Co-Chair Mining and Learning with Graphs ( MLG-2006 )
Steering Committee member Mining and Learning with Graphs ( MLG-2007 | MLG-2008 )
Guest Editor Machine Learning special issue on Mining and Learning with Graphs
Tutorials, Colloquia, Invited Talks, ...
- Machine Learning tutorial at the 2008 workshop of the DFG program Organic Computing
- Kernel Methods in Machine Learning tutorial at the Estonian Summer School in Computer and Systems Science (2006)
- Kernels for Structured Data at the workshop Learning Structured Information in Natural Language Applications (held with EACL'06)
- Mining Graph Data with Kernel Methods at the 4th Workshop on Multi-Relational Data Mining (held with KDD'05)
- Dagstuhl seminar: Probabilistic, Logical and Relational Learning
- ICML Tutorial: Kernels for Structured Data The application of kernel methods to data that has no natural representation in a Euclidean space, requires the definition of positive definite functions on such data. This tutorial describes the state of the art of a field emerging as the intersection between kernel methods and structured data. The primary goal of this tutorial is to give the audience a coherent overview of the different approaches of applying kernel methods to structured data. It emphasises the conceptual similarities and differences rather than the technical details of the different approaches (more details).
- An Introduction to Kernel Methods for Mining Graph Data at the research colloquium, TU Berlin.
- An Introduction to Kernel Methods for Mining Graph Data at the First International Workshop on Mining Graphs, Trees and Sequences (held with ECML/PKDD'03).
- Bestimmung der Skelettstruktur von Diterpenen durch NMR-Analyse at the biomathematical colloquium, Bonn University. [abstract]
- Kernel-Based Learning from Structured Data at the 2002 Summer School on Relational Data Mining in Helsinki. [handouts]
Programm Committee Membership
- European Conference on Machine Learning ( Area Chair ECML-2006 | Area Chair ECML-2007 | ECML-2008 | Area Chair ECML-2009 )
- International Joint Conference on Artificial Intelligence ( IJCAI-2009 )
- International Conference on Machine Learning ( ICML-2002 | ICML-2005 | ICML-2006 | ICML-2008 | ICML-2009 )
- International Conference on Knowledge Discovery and Data Mining ( KDD-2004 | KDD-2005 | KDD-2008 | KDD-2009 )
- International Workshop on Mining and Learning with Graphs ( MLG-2009 )
- International Workshop on Mining Graphs, Trees and Sequences ( MGTS-2003 | MGTS-2004 | MGTS-2005 )
- Workshop on Multi-Relational Data Mining ( MRDM-2005 | MRDM-2007 )
- Workshop on Mining Graphs and Complex Structures (MGCS-2007)
Reviewing
- MLJ
- JMLR
- JAIR
- NIPS ( 04 | 05 | 06 | 07 | 08 )
- IJCAI ( 05 )
- COLT
- AAAI
- KDD
- ECML/PKDD
- SIAM SDM
- ICML
- JCIM
Research Proposal Evaluation The Israel Science Foundation ( ISF )
Visits (of varying lengths --- between a few hours and a few months)
- University of Bristol (11/2007)
- HIIT Helsinki (10/2007)
- MPI Tübingen (11/2006)
- University of Bristol (06/2006)
- University of Wisconsin (08/2005)
- National ICT Australia (03-05/2005)
- TU Berlin (02/2004)
- University of Freiburg (02/2003)
- University of Leuven (04/2003)

[ Overview | Publications | Activities | Research Interests ]

Research Interests

Machine Learning
- Kernel Methods
- Mining and Learning with Graphs
- Semi-Supervised and Transductive Learning
- Ranking (on Graphs)

[ Overview | Publications | Activities | Research Interests ]

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