A

Amodeo, G. ; Blanco, R. ; 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]

B

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

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

Brefeld, U. ; Cambazoglu, B. B. ; 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]

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

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

Brefeld, U. ; Haider, P. ; 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]

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

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

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

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

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

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

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

Bickel, S. ; Brefeld, U. ; Faulstich, L. ; Hakenberg, J. ; Leser, U. ; Plake, C. ; 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]

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

F

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

G

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

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

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

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

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

Geibel, P. ; Brefeld, U. ; 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]

H

Haider, P. ; Chiarandini, L. ; 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. ; Chiarandini, L. ; Brefeld, U. ; 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]

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

Haider, P. ; Brefeld, U. ; 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]

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

K

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

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

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

Kloft, M. ; Brefeld, U. ; Sonnenburg, S. ; 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]

Kloft, M. ; Brefeld, U. ; Sonnenburg, S. ; Zien, A. ; Laskov, P. ; 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]

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

Klein, T. ; Brefeld, U. ; 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. ; Brefeld, U. ; Laskov, P. ; 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]

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

N

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

R

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

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

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

T

Tavakol, Maryam (2019):
Contextual Models for Sequential Recommendation.
Darmstadt, Technische Universität,
[Ph.D. Thesis]

Z

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