"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

Publications

Some selected publications are listed below. I am trying to keep the complete list up to date, though you should also look [@DBLP], [@springer], [@scholar], or [@acm]. Now there is also a list [@microsoft academic search] as well as [@scholar/citations].

• Mario Boley, Sandy Moens, Thomas Gärtner. Linear Space Direct Pattern Sampling using Coupling From The Past. Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, page 69-77. 2012. ACM. [ software | slides | BibTeX ]
• J. Humrich, T. Gärtner, Gemma C. Garriga. A Fixed Parameter Tractable Integer Program for Finding the Maximum Order Preserving Submatrix. 11th IEEE International Conference on Data Mining, ICDM, 2011. [ BibTeX ]
• Olana Missura, Thomas Gärtner. Predicting Dynamic Difficulty. In J. Shawe-Taylor, R.S. Zemel, P. Bartlett, F.C.N. Pereira, K.Q. Weinberger, editor(s), Advances in Neural Information Processing Systems 24, page 2007-2015. 2011. [ @nips | BibTeX ]
• Mario Boley, Claudio Lucchese, Daniel Paurat, Thomas Gärtner. Direct Local Pattern Sampling by Efficient Two-Step Random Procedures. The 17th annual ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011. [ BibTeX ]
• Mario Boley, Henrik Grosskreutz, Thomas Gärtner. Formal Concept Sampling for Counting and Threshold-Free Local Pattern Mining. Proc. of the SIAM Int. Conf. on Data Mining (SDM 2010), 2010. SIAM. [ electr.edt. | 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 ]
• 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 ]
• Shankar Vembu, Thomas Gärtner, Mario Boley. Probabilistic Structured Predictors. Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence (UAI), 2009. [ pdf | 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 ]
• Karina Zapien, Thomas Gärtner, Gilles Gasso, Stephane 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 ]
• 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, Yasemin Altun. Transductive Gaussian Process Regression with Automatic Model Selection. Proceedings of the 17th European Conference on Machine Learning, 2006. Springer-Verlag. [ @springer | 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. Simpler Knowledge-based Support Vector Machines. Proceedings of the 23rd International Conference on Machine Learning, 2006. ACM Press. [ @imls | 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. Kernels for Structured Data. Universität Bonn, 2005. [ buy it from amazon.de, amazon.co.uk, or elsewhere ]. [ 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, John W. Lloyd, Peter A. Flach. Kernels and Distances for Structured Data. Machine Learning, 2004. [ @springer | BibTeX ]
• Thomas Gärtner. A Survey of Kernels for Structured Data. SIGKDD Explorations, 2003. [ @portal.acm | @sigkdd | 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, 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, 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 ]