TU Darmstadt / ULB / TUbiblio

Browse by Person

Up a level
Export as [feed] Atom [feed] RSS 1.0 [feed] RSS 2.0
Group by: No Grouping | Item Type | Date | Language
Number of items: 14.

Article

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]

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]

Conference or Workshop Item

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]

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]

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]

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]

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]

Report

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]

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]

This list was generated on Sat Dec 7 00:19:57 2019 CET.