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Number of items: 50.

Haider, P. and Chiarandini, L. and Brefeld, U. (2012):
Discriminative Clustering for Market Segmentation.
In: Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining, [Conference or Workshop Item]

Haider, P. and Chiarandini, L. and Brefeld, U. and Jaimes, A. (2012):
Dynamic Contextual Models for User Interaction on the Web.
In: ECML/PKDD Workshop on Mining and Exploiting Interpretable Local Patterns (I-PAT), [Conference or Workshop Item]

Binder, A. and Nakajima, S. and Kloft, M. and Müller, C. and Samek, W. and Brefeld, U. and Müller, K.-R. and Kawanabe, M. (2012):
Insights from Classifying Visual Concepts with Multiple Kernel Learning.
In: PLoS ONE, 7(8):e38897, [Article]

Görnitz, N. and Kloft, M. and Rieck, K. and Brefeld, U. (2012):
Toward Supervised Anomaly Detection.
In: Journal of Artificial Intelligence Research, accepted, [Article]

Haider, P. and Chiarandini, L. and Brefeld, U. (2011):
Behavioral User Models for Yahoo! News.
In: Proceedings of TechPulse, [Conference or Workshop Item]

Brefeld, U. and Cambazoglu, B. B. and Junqueira, F. P. (2011):
Document Assignment in Multi-Site Search Engines.
In: Proceedings of the International Conference on Web Search and Data Mining, [Conference or Workshop Item]

Amodeo, G. and Blanco, R. and Brefeld, U. (2011):
Hybrid Models for Future Event Prediction.
In: Proceedings of the International ACM Conference on Information and Knowledge Management, [Conference or Workshop Item]

Binder, A. and Nakajima, S. and Kloft, M. and Müller, C. and Samek, W. and Brefeld, U. and Müller, K.-R. and Kawanabe, M. (2011):
Insights from Classifying Visual Concepts with Multiple Kernel Learning.
[Report]

Fernandes, E. R. and Brefeld, U. (2011):
Learning from Partially Annotated Sequences.
In: Proceedings of the European Conference on Machine Learning, [Conference or Workshop Item]

Giannopoulos, G. and Brefeld, U. and Dalamagas, T. and Sellis, T. (2011):
Learning to Rank User Intent.
In: Proceedings of the International ACM Conference on Information and Knowledge Management, [Conference or Workshop Item]

Rathke, F. and Hansen, K. and Brefeld, U. and Müller, K.-R. (2011):
StructRank: A New Approach for Ligand-Based Virtual Screening.
51, In: Journal of Chemical Information Modeling, pp. 83-92, [Article]

Kloft, M. and Brefeld, U. and Sonnenburg, S. and Zien, A. (2011):
lp-Norm Multiple Kernel Learning.
12(Mar), In: Journal of Machine Learning Research, pp. 953-997, [Article]

Rieck, K. and Krüger, T. and Brefeld, U. and Müller, K.-R. (2010):
Approximate Tree Kernels.
11, In: Journal of Machine Learning Research, pp. 555-580, [Article]

Kloft, M. and Brefeld, U. and Sonnenburg, S. and Laskov, P. and Müller, K.-R. and Zien, A. (2010):
Efficient and Accurate $ell_p$-norm Multiple Kernel Learning.
In: Advances in Neural Information Processing Systems, [Conference or Workshop Item]

Brefeld, U. and Getoor, L. and Macskassy, S. A. (2010):
Eighth workshop on mining and learning with graphs.
12(2), In: SIGKDD Explorations, pp. 63-65, [Article]

Brefeld, U. and Getoor, L. and Macskassy, S. A. (eds.) (2010):
MLG 2010: Proceedings of the Eighth Workshop on Mining and Learning with Graphs.
New York, NY, USA, ACM, [Book]

Kloft, M. and Brefeld, U. and Sonnenburg, S. and Zien, A. (2010):
Non-Sparse Regularization and Efficient Training with Multiple Kernels.
(UCB/EECS-2010-21), [Report]

Görnitz, N. and Kloft, M. and Rieck, K. and Brefeld, U. (2009):
Active Learning for Network Intrusion Detection.
In: Proceedings of the CCS Workshop on Security and Artificial Intelligence, [Conference or Workshop Item]

Görnitz, N. and Kloft, M. and Brefeld, U. (2009):
Active and Semi-supervised Data Domain Description.
In: Proceedings of the European Conference on Machine Learning, [Conference or Workshop Item]

Kloft, M. and Brefeld, U. and Sonnenburg, S. and Zien, A. (2009):
Comparing Sparse and Non-sparse Multiple Kernel Learning.
In: Proceedings of the NIPS Workshop on Understanding Multiple Kernel Learning Methods, [Conference or Workshop Item]

Binder, A. and Kawanabe, M. and Brefeld, U. (2009):
Efficient Classification of Images with Taxonomies.
In: Proceedings of the Asian Conference on Computer Vision, [Conference or Workshop Item]

Kloft, M. and Nakajima, S. and Brefeld, U. (2009):
Feature Selection for Density Level-Sets.
In: Proceedings of the European Conference on Machine Learning, [Conference or Workshop Item]

Kloft, M. and Brefeld, U. and Sonnenburg, S. and Zien, A. and Laskov, P. and Müller, K.-R. (2009):
Learning Non-Sparse Kernel Mixtures.
In: Proceedings of the PASCAL2 Workshop on Sparsity in Machine Learning and Statistics, [Conference or Workshop Item]

Nakajima, S. and Binder, A. and Müller, C. and Wojcikiewicz, W. and Kloft, M. and Brefeld, U. and Müller, K.-R. and Kawanabe, M. (2009):
Multiple Kernel Learning for Object Classification.
In: Proceedings of the 12th Workshop on Information-based Induction Sciences, [Conference or Workshop Item]

Brefeld, U. and Piskorski, J. and Yangarber, R. (eds.) (2009):
Proceedings of the UCMedia Workshop on Mining User Generated Content for Security.
[Book]

Rieck, K. and Brefeld, U. and Krüger, T. (2008):
Approximate Kernels for Trees.
(5/2008), [Report]

Kloft, M. and Brefeld, U. and Düssel, P. and Gehl, C. and Laskov, P. (2008):
Automatic feature selection for anomaly detection.
In: Proceedings of the First ACM Workshop on AISec, [Conference or Workshop Item]

Klein, T. and Brefeld, U. and Scheffer, T. (2008):
Exact and approximate inference for annotating graphs with structural {SVMs}.
In: Proceedings of the European Conference on Machine Learning, [Conference or Workshop Item]

Kloft, M. and Brefeld, U. and Laskov, P. and Sonnenburg, S. (2008):
Non-sparse multiple kernel learning.
In: Proceedings of the NIPS Workshop on Kernel Learning: Automatic Selection of Optimal Kernels, [Conference or Workshop Item]

Blohm, S. and Brefeld, U. and Jungermann, F. and Yangarber, R. (eds.) (2008):
Proceedings of the {ECML} Workshop on High-level Information Extraction.
[Book]

Brefeld, U. and Haider, P. and Scheffer, T. (2007):
Supervised clustering for spam detection in data streams.
In: Proceedings of the NIPS Workshop on Machine Learning in Adversarial Environments for Computer Security, [Conference or Workshop Item]

Haider, P. and Brefeld, U. and Scheffer, T. (2007):
Supervised clustering of streaming data for email batch detection.
In: Proceedings of the International Conference on Machine Learning, [Conference or Workshop Item]

Brefeld, U. and Klein, T. and Scheffer, T. (2007):
Support vector machines for collective inference.
In: Proceedings of the Workshop on Mining and Learning with Graphs, [Conference or Workshop Item]

Zien, A. and Brefeld, U. and Scheffer, T. (2007):
Transductive support vector machines for structured variables.
In: Proceedings of the International Conference on Machine Learning, [Conference or Workshop Item]

Brefeld, U. and Gärtner, T. and Scheffer, T. and Wrobel, S. (2006):
Efficient co-regularised least squares regression.
In: Proceedings of the International Conference on Machine Learning, [Conference or Workshop Item]

Brefeld, U. and Joachims, T. and Taskar, B. and Xing, E. P. (eds.) (2006):
Proceedings of the {ICML} Workshop on Learning in Structured Output Spaces.
[Book]

Brefeld, U. and Scheffer, T. (2006):
Semi-supervised learning for structured output variables.
In: Proceedings of the International Conference on Machine Learning, [Conference or Workshop Item]

Hakenberg, J. and Bickel, S. and Plake, C. and Brefeld, U. and Zahn, H. and Faulstich, L. and Leser, U. and Scheffer, T. (2005):
Systematic feature evaluation for gene name recognition.
6(1), In: BMC Bioinformatics, ISSN 1471-2105, DOI: 10.1186/1471-2105-6-S1-S9,
[Article]

Brefeld, U. and Scheffer, T. (2005):
{AUC} maximizing support vector learning.
In: Proceedings of the ICML Workshop on ROC Analysis in Machine Learning, [Conference or Workshop Item]

Brefeld, U. and Büscher, C. and Scheffer, T. (2005):
Multi-view Hidden Markov Perceptrons.
In: Proceedings of the German Workshop on Machine Learning (FGML), [Conference or Workshop Item]

Brefeld, U. and Büscher, C. and Scheffer, T. (2005):
Multi-view discriminative sequential learning.
In: Proceedings of the European Conference on Machine Learning, [Conference or Workshop Item]

Brefeld, U. and Scheffer, T. (2004):
Co-{EM} support vector learning.
In: Proceedings of the International Conference on Machine Learning, [Conference or Workshop Item]

Jantke, Klaus P. and Grieser, Gunter and Lange, Steffen and Memmel, Martin Abecker, A. and Bickel, S. and Brefeld, U. and Drost, I. and Henze, N. and Herden, O. and Minor, M. and Scheffer, Tobias and Stojanovic, L. and Weibelzahl, S. (eds.) (2004):
DaMiT: Data Mining lernen und lehren.
In: LWA 2004, Lernen -- Wissensentdeckung -- Adaptivität, 4.-6.Oktober 2004, pp. 171-179, [Conference or Workshop Item]

Fürnkranz, Johannes Abecker, A. and Bickel, S. and Brefeld, U. and Drost, I. and Henze, N. and Herden, O. and Minor, M. and Scheffer, Tobias and Stojanovic, L. and Weibelzahl, S. (eds.) (2004):
Modeling Rule Precision.
In: Lernen -- Wissensentdeckung --- Adaptivität. Proceedings of the LWA-04 Workshops, pp. 147-154, [Online-Edition: http://www.ke.informatik.tu-darmstadt.de/~juffi/publications...],
[Conference or Workshop Item]

Brefeld, U. and Bickel, S. and Scheffer, T. (2004):
Multi-View Lernen.
In: Proceedings of the German Workshop on Machine Learning (FGML), [Conference or Workshop Item]

Geibel, P. and Brefeld, U. and Wysotzki, F. (2004):
Perceptron and {SVM} Learning with Generalized Cost Models.
8(5), In: Intelligent Data Analysis, pp. 439-455, [Article]

Abecker, A. and Bickel, S. and Brefeld, U. and Drost, I. and Henze, N. and Herden, O. and Minor, M. and Scheffer, T. and Stojanovic, L. and Weibelzahl, S. (eds.) (2004):
Proceedings of the Workshops on Learning, Knowledge Discovery, and Adaptivity (LWA).
[Book]

Bickel, S. and Brefeld, U. and Faulstich, L. and Hakenberg, J. and Leser, U. and Plake, C. and Scheffer, T. (2004):
A Support Vector Machine Classifier for Gene Name Recognition.
In: Proceedings of BioCreative / EMBO Workshop: A Critical Assessment of Text Mining Methods in Molecular Biology, [Conference or Workshop Item]

Geibel, P. and Brefeld, U. and Wysotzki, F. (2003):
Learning linear classifiers sensitive to example dependent and noisy costs.
In: Proceedings of the International Symposium on Intelligent Data Analysis, [Conference or Workshop Item]

Brefeld, U. and Geibel, P. and Wysotzki, F. (2003):
Support vector machines with example dependent costs.
In: Proceedings of the European Conference on Machine Learning, [Conference or Workshop Item]

This list was generated on Tue Dec 10 01:06:27 2019 CET.