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Note: Links lead to the DBLP on the Web. Tobias Scheffer 22 Mark-A. Krogel , Tobias Scheffer: Effectiveness of information extraction, multi-relational, and multi-view learning for prediction gene deletion experiments. BIOKDD 2003 : 10-16 21 Tobias Scheffer, Stefan Wrobel : A Scalable Constant-Memory Sampling Algorithm for Pattern Discovery in Large Databases. PKDD 2002 : 397-409 20 Tobias Scheffer, Stefan Wrobel , Borislav Popov , Damyan Ognianov , Christian Decomain , Susanne Hoche : Lerning Hidden Markov Models for Information Extraction Actively from Partially Labeled Text. KI 16 (2): 17-22 (2002) 19 Mark-A. Krogel , Marcus Denecke , Marco Landwehr , Tobias Scheffer: Combining Data and Text Mining Techniques for Yeast Gene Regulation Prediction: A Case Study. SIGKDD Explorations 4 (2): 104-105 (2002) 18 Hans Gründel , Tino Naphtali , Christian Wiech , Jan-Marian Gluba , Maiken Rohdenburg , Tobias Scheffer: Clipping and Analyzing News Using Machine Learning Techniques. Discovery Science 2001 : 87-99 17 Tobias Scheffer, Christian Decomain , Stefan Wrobel : Mining the Web with Active Hidden Markov Models. ICDM 2001 : 645-646 16 Tobias Scheffer, Stefan Wrobel : Incremental Maximization of Non-Instance-Averaging Utility Functions with Applications to Knowledge Discovery Problems. ICML 2001 : 481-488 15 Tobias Scheffer, Christian Decomain , Stefan Wrobel : Active Hidden Markov Models for Information Extraction. IDA 2001 : 309-318 14 Tobias Scheffer: Finding Association Rules That Trade Support Optimally against Confidence. PKDD 2001 : 424-435 13 Tobias Scheffer: Average-Case Analysis of Classification Algorithms for Boolean Functions and Decision Trees. ALT 2000 : 194-208 12 Tobias Scheffer: Nonparametric Regularization of Decision Trees. ECML 2000 : 344-356 11 Tobias Scheffer: Predicting the Generalization Performance of Cross Validatory Model Selection Criteria. ICML 2000 : 831-838 10 Tobias Scheffer, Stefan Wrobel : A sequential sampling algorithm for a general class of utility criteria. KDD 2000 : 330-334 9 Andrew R. Mitchell , Tobias Scheffer, Arun Sharma , Frank Stephan : The VC-Dimension of Subclasses of Pattern. ATL 1999 : 93-105 8 Tobias Scheffer, Thorsten Joachims : Expected Error Analysis for Model Selection. ICML 1999 : 361-370 7 Tobias Scheffer: Error Estimation and Model Selection. KI 13 (3): 46-48 (1999) 6 Tobias Scheffer: International Conference on Machine Learning (ICML-99). KI 13 (4): 68 (1999) 5 Tobias Scheffer, Thorsten Joachims : Estimating the Expected Error of Empirical Minimizers for Model Selection. AAAI/IAAI 1998 : 1200 4 Tobias Scheffer, Russell Greiner , Christian Darken : Why Experimentation can be better than "Perfect Guidance". ICML 1997 : 331-339 3 Tobias Scheffer, Ralf Herbrich : Unbiased Assesment of Learning Algorithms. IJCAI (2) 1997 : 798-803 2 Tobias Scheffer, Ralf Herbrich , Fritz Wysotzki : Efficient Theta-Subsumption Based on Graph Algorithms. Inductive Logic Programming Workshop 1996 : 212-228 1 Tobias Scheffer: A Generic Algorithm for Learning Rules with Hierarchical Exceptions. SBIA 1995 : 181-190  DiSC'03 © 2003 Association for Computing Machinery |
