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Tobias Scheffer Vis

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*2009
68EEPeter Haider, Tobias Scheffer: Bayesian clustering for email campaign detection. ICML 2009: 49
67EESzymon Jaroszewicz, Tobias Scheffer, Dan A. Simovici: Scalable pattern mining with Bayesian networks as background knowledge. Data Min. Knowl. Discov. 18(1): 56-100 (2009)
2008
66EEThoralf Klein, Ulf Brefeld, Tobias Scheffer: Exact and Approximate Inference for Annotating Graphs with Structural SVMs. ECML/PKDD (1) 2008: 611-623
65EEUwe Dick, Peter Haider, Tobias Scheffer: Learning from incomplete data with infinite imputations. ICML 2008: 232-239
64EESteffen Bickel, Jasmina Bogojeska, Thomas Lengauer, Tobias Scheffer: Multi-task learning for HIV therapy screening. ICML 2008: 56-63
63EESteffen Bickel, Christoph Sawade, Tobias Scheffer: Transfer Learning by Distribution Matching for Targeted Advertising. NIPS 2008: 145-152
62EESzymon Jaroszewicz, Lenka Ivantysynova, Tobias Scheffer: Schema matching on streams with accuracy guarantees. Intell. Data Anal. 12(3): 253-270 (2008)
2007
61EEAlexander Zien, Ulf Brefeld, Tobias Scheffer: Transductive support vector machines for structured variables. ICML 2007: 1183-1190
60EELaura Dietz, Steffen Bickel, Tobias Scheffer: Unsupervised prediction of citation influences. ICML 2007: 233-240
59EEPeter Haider, Ulf Brefeld, Tobias Scheffer: Supervised clustering of streaming data for email batch detection. ICML 2007: 345-352
58EESteffen Bickel, Michael Brückner, Tobias Scheffer: Discriminative learning for differing training and test distributions. ICML 2007: 81-88
57EEDavid S. Vogel, Ognian Asparouhov, Tobias Scheffer: Scalable look-ahead linear regression trees. KDD 2007: 757-764
56EEUlf Brefeld, Thoralf Klein, Tobias Scheffer: Support Vector Machines for Collective Inference. MLG 2007
2006
55 Johannes Fürnkranz, Tobias Scheffer, Myra Spiliopoulou: Machine Learning: ECML 2006, 17th European Conference on Machine Learning, Berlin, Germany, September 18-22, 2006, Proceedings Springer 2006
54 Johannes Fürnkranz, Tobias Scheffer, Myra Spiliopoulou: Knowledge Discovery in Databases: PKDD 2006, 10th European Conference on Principles and Practice of Knowledge Discovery in Databases, Berlin, Germany, September 18-22, 2006, Proceedings Springer 2006
53EEUlf Brefeld, Thomas Gärtner, Tobias Scheffer, Stefan Wrobel: Efficient co-regularised least squares regression. ICML 2006: 137-144
52EEUlf Brefeld, Tobias Scheffer: Semi-supervised learning for structured output variables. ICML 2006: 145-152
51EESteffen Bickel, Tobias Scheffer: Dirichlet-Enhanced Spam Filtering based on Biased Samples. NIPS 2006: 161-168
50EEMichael Brückner, Peter Haider, Tobias Scheffer: Highly Scalable Discriminative Spam Filtering. TREC 2006
2005
49 Achim G. Hoffmann, Hiroshi Motoda, Tobias Scheffer: Discovery Science, 8th International Conference, DS 2005, Singapore, October 8-11, 2005, Proceedings Springer 2005
48EESteffen Bickel, Tobias Scheffer: Estimation of Mixture Models Using Co-EM. ECML 2005: 35-46
47EESteffen Bickel, Peter Haider, Tobias Scheffer: Learning to Complete Sentences. ECML 2005: 497-504
46EEUlf Brefeld, Christoph Büscher, Tobias Scheffer: Multi-view Discriminative Sequential Learning. ECML 2005: 60-71
45EEIsabel Drost, Tobias Scheffer: Thwarting the Nigritude Ultramarine: Learning to Identify Link Spam. ECML 2005: 96-107
44EEIsabel Drost, Steffen Bickel, Tobias Scheffer: Discovering Communities in Linked Data by Multi-view Clustering. GfKl 2005: 342-349
43EESteffen Bickel, Peter Haider, Tobias Scheffer: Predicting Sentences using N-Gram Language Models. HLT/EMNLP 2005
42EESzymon Jaroszewicz, Tobias Scheffer: Fast discovery of unexpected patterns in data, relative to a Bayesian network. KDD 2005: 118-127
41 Ulf Brefeld, Christoph Büscher, Tobias Scheffer: Multi-View Hidden Markov Perceptrons. LWA 2005: 134-138
40EETobias Scheffer: Multi-View Learning and Link Farm Discovery. Probabilistic, Logical and Relational Learning 2005
39EEJörg Hakenberg, Steffen Bickel, Conrad Plake, Ulf Brefeld, Hagen Zahn, Lukas Faulstich, Ulf Leser, Tobias Scheffer: Systematic feature evaluation for gene name recognition. BMC Bioinformatics 6(S-1): (2005)
38EETobias Scheffer: Finding association rules that trade support optimally against confidence. Intell. Data Anal. 9(4): 381-395 (2005)
37EEDavid S. Vogel, Steffen Bickel, Peter Haider, Rolf Schimpfky, Peter Siemen, Steve Bridges, Tobias Scheffer: Classifying search engine queries using the web as background knowledge. SIGKDD Explorations 7(2): 117-122 (2005)
2004
36 Andreas Abecker, Steffen Bickel, Ulf Brefeld, Isabel Drost, Nicola Henze, Olaf Herden, Mirjam Minor, Tobias Scheffer, Ljiljana Stojanovic, Stephan Weibelzahl: LWA 2004: Lernen - Wissensentdeckung - Adaptivität, Berlin, 4. - 6. Oktober 2004, Workshopwoche der GI-Fachgruppen/Arbeitskreise (1) Fachgruppe Adaptivität und Benutzermodellierung in Interaktiven Softwaresystemen (ABIS 2004), (2) Arbeitskreis Knowledge Discovery (AKKD 2004), (3) Fachgruppe Maschinelles Lernen (FGML 2004), (4) Fachgruppe Wissens- und Erfahrungsmanagement (FGWM 2004) Humbold-Universität Berlin 2004
35EESteffen Bickel, Tobias Scheffer: Learning from Message Pairs for Automatic Email Answering. ECML 2004: 87-98
34EESteffen Bickel, Tobias Scheffer: Multi-View Clustering. ICDM 2004: 19-26
33EEUlf Brefeld, Tobias Scheffer: Co-EM support vector learning. ICML 2004
32 Tobias Scheffer: Workshop der GI-Fachgruppe "Maschinelles Lernen" (FGML). LWA 2004: 110
31 Ulf Brefeld, Steffen Bickel, Tobias Scheffer: Multi-View Lernen. LWA 2004: 131
30 Isabel Drost, Tobias Scheffer: Efficiency and Stability of Clustering Algorithms for Linked Data. LWA 2004: 146
29EEKorinna Grabski, Tobias Scheffer: Sentence completion. SIGIR 2004: 433-439
28EETobias Scheffer: Email answering assistance by semi-supervised text classification. Intell. Data Anal. 8(5): 481-493 (2004)
27EEMark-A. Krogel, Tobias Scheffer: Multi-Relational Learning, Text Mining, and Semi-Supervised Learning for Functional Genomics. Machine Learning 57(1-2): 61-81 (2004)
2003
26EEMark-A. Krogel, Tobias Scheffer: Effectiveness of information extraction, multi-relational, and multi-view learning for prediction gene deletion experiments. BIOKDD 2003: 10-16
25EEMark-A. Krogel, Tobias Scheffer: Effectiveness of Information Extraction, Multi-Relational, and Semi-Supervised Learning for Predicting Functional Properties of Genes. ICDM 2003: 569-572
24EEMichael Kockelkorn, Andreas Lüneburg, Tobias Scheffer: Learning to Answer Emails. IDA 2003: 25-35
23EEMichael Kockelkorn, Andreas Lüneburg, Tobias Scheffer: Using Transduction and Multi-view Learning to Answer Emails. PKDD 2003: 266-277
2002
22EETobias Scheffer, Stefan Wrobel: A Scalable Constant-Memory Sampling Algorithm for Pattern Discovery in Large Databases. PKDD 2002: 397-409
21EETobias Scheffer, Stefan Wrobel: Finding the Most Interesting Patterns in a Database Quickly by Using Sequential Sampling. Journal of Machine Learning Research 3: 833-862 (2002)
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)
19EEMark-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)
2001
18EEHans 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
17EETobias 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
15EETobias Scheffer, Christian Decomain, Stefan Wrobel: Active Hidden Markov Models for Information Extraction. IDA 2001: 309-318
14EETobias Scheffer: Finding Association Rules That Trade Support Optimally against Confidence. PKDD 2001: 424-435
2000
13EETobias Scheffer: Average-Case Analysis of Classification Algorithms for Boolean Functions and Decision Trees. ALT 2000: 194-208
12EETobias 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
10EETobias Scheffer, Stefan Wrobel: A sequential sampling algorithm for a general class of utility criteria. KDD 2000: 330-334
1999
9EEAndrew 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)
1998
5 Tobias Scheffer, Thorsten Joachims: Estimating the Expected Error of Empirical Minimizers for Model Selection. AAAI/IAAI 1998: 1200
1997
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
1996
2 Tobias Scheffer, Ralf Herbrich, Fritz Wysotzki: Efficient Theta-Subsumption Based on Graph Algorithms. Inductive Logic Programming Workshop 1996: 212-228
1995
1 Tobias Scheffer: A Generic Algorithm for Learning Rules with Hierarchical Exceptions. SBIA 1995: 181-190

Coauthor Index

1Andreas Abecker [36]
2Ognian Asparouhov [57]
3Steffen Bickel [31] [34] [35] [36] [37] [39] [43] [44] [47] [48] [51] [58] [60] [63] [64]
4Jasmina Bogojeska [64]
5Ulf Brefeld [31] [33] [36] [39] [41] [46] [52] [53] [56] [59] [61] [66]
6Steve Bridges [37]
7Michael Brückner [50] [58]
8Christoph Büscher [41] [46]
9Christian Darken [4]
10Christian Decomain [15] [17] [20]
11Marcus Denecke [19]
12Uwe Dick [65]
13Laura Dietz [60]
14Isabel Drost [30] [36] [44] [45]
15Lukas Faulstich [39]
16Johannes Fürnkranz [54] [55]
17Thomas Gärtner [53]
18Jan-Marian Gluba [18]
19Korinna Grabski [29]
20Russell Greiner [4]
21Hans Gründel [18]
22Peter Haider [37] [43] [47] [50] [59] [65] [68]
23Jörg Hakenberg [39]
24Nicola Henze [36]
25Ralf Herbrich [2] [3]
26Olaf Herden [36]
27Susanne Hoche [20]
28Achim G. Hoffmann [49]
29Lenka Ivantysynova [62]
30Szymon Jaroszewicz [42] [62] [67]
31Thorsten Joachims [5] [8]
32Thoralf Klein [56] [66]
33Michael Kockelkorn [23] [24]
34Mark-A. Krogel [19] [25] [26] [27]
35Marco Landwehr [19]
36Thomas Lengauer [64]
37Ulf Leser [39]
38Andreas Lüneburg [23] [24]
39Mirjam Minor [36]
40Andrew R. Mitchell [9]
41Hiroshi Motoda [49]
42Tino Naphtali [18]
43Damyan Ognianov [20]
44Conrad Plake [39]
45Borislav Popov [20]
46Maiken Rohdenburg [18]
47Christoph Sawade [63]
48Rolf Schimpfky [37]
49Arun Sharma [9]
50Peter Siemen [37]
51Dan A. Simovici [67]
52Myra Spiliopoulou [54] [55]
53Frank Stephan [9]
54Ljiljana Stojanovic [36]
55David S. Vogel [37] [57]
56Stephan Weibelzahl [36]
57Christian Wiech [18]
58Stefan Wrobel [10] [15] [16] [17] [20] [21] [22] [53]
59Fritz Wysotzki [2]
60Hagen Zahn [39]
61Alexander Zien [61]

Colors in the list of coauthors

Copyright © Tue Nov 3 08:52:44 2009 by Michael Ley (ley@uni-trier.de)