Ulf Brefeld

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Marius KloftTU KaiserslauternVerified email at cs.uni-kl.de
Soeren SonnenburgMachine Learning ResearcherVerified email at tomtom.com
Klaus-Robert MüllerTU Berlin & Korea University & Google Brain & MPIIVerified email at tu-berlin.de
Nico GoernitzCTO @ MorphAIs | former PostDoc @ TU-BerlinVerified email at tu-berlin.de
Konrad RieckProfessor of Computer Science, TU BraunschweigVerified email at tu-bs.de
Maryam TavakolEindhoven University of TechnologyVerified email at tue.nl
Pavel LaskovUniversity of LiechtensteinVerified email at uni.li
Alexander BinderAssociate Professor, Singapore Institute of Technology (SIT) and University of Oslo (UiO)Verified email at singaporetech.edu.sg
Shinichi NakajimaMachine Learning Group, Technische Universität BerlinVerified email at tu-berlin.de
Motoaki KawanabeSenior Researcher, Advanced Telecommunications Research Institute InternationalVerified email at atr.jp
Thomas GärtnerTU Wien (Technical University of Vienna)Verified email at tuwien.ac.at
Steffen BickelNokia Gate5 GmbHVerified email at cs.uni-potsdam.de
Jörg HakenbergIllumina, Inc.Verified email at illumina.com
Ulf LeserKnowledge Management in Bioinformatics, Humboldt-Universität zu BerlinVerified email at informatik.hu-berlin.de
Tammo KruegerTU BerlinVerified email at tu-berlin.de
Roi BlancoAmazonVerified email at udc.es
Eraldo R. FernandesLeuphana University of LüneburgVerified email at leuphana.de
Jamal Abdul NasirAssistant Professor, National University of Ireland Galway, IrelandVerified email at nuigalway.ie
Luca ChiarandiniGoogle IncVerified email at google.com
Patrick DuesselViacomCBSVerified email at riskbeam.io

Ulf Brefeld

Leuphana Universität Lüneburg

Verified email at leuphana.de - Homepage

Machine Learning


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l_p-Norm Multiple Kernel Learning M Kloft, U Brefeld, S Sonnenburg, A Zien The Journal of Machine Learning Research 12, 953-997, 2011	426	2011
Toward supervised anomaly detection N Görnitz, M Kloft, K Rieck, U Brefeld Journal of Artificial Intelligence Research 46, 235-262, 2013	354	2013
Efficient and accurate lp-norm multiple kernel learning M Kloft, U Brefeld, P Laskov, KR Müller, A Zien, S Sonnenburg Advances in neural information processing systems 22, 2009	346	2009
Co-EM support vector learning U Brefeld, T Scheffer Proceedings of the twenty-first international conference on Machine learning, 16, 2004	223	2004
Efficient co-regularised least squares regression U Brefeld, T Gärtner, T Scheffer, S Wrobel Proceedings of the 23rd international conference on Machine learning, 137-144, 2006	217	2006
AUC maximizing support vector learning U Brefeld, T Scheffer Proceedings of the ICML 2005 workshop on ROC Analysis in Machine Learning, 2005	184	2005
Non-sparse multiple kernel learning M Kloft, U Brefeld, P Laskov, S Sonnenburg NIPS Workshop on Kernel Learning: Automatic Selection of Optimal Kernels 4, 5, 2008	125	2008
Semi-supervised learning for structured output variables U Brefeld, T Scheffer Proceedings of the 23rd international conference on Machine learning, 145-152, 2006	95	2006
Support vector machines with example dependent costs U Brefeld, P Geibel, F Wysotzki European Conference on Machine Learning, 23-34, 2003	95	2003
Active learning for network intrusion detection N Görnitz, M Kloft, K Rieck, U Brefeld Proceedings of the 2nd ACM workshop on Security and artificial intelligence …, 2009	86	2009
Multi-view discriminative sequential learning U Brefeld, C Büscher, T Scheffer European Conference on Machine Learning, 60-71, 2005	70	2005
Factored MDPs for detecting topics of user sessions M Tavakol, U Brefeld Proceedings of the 8th ACM Conference on Recommender Systems, 33-40, 2014	69	2014
Automatic feature selection for anomaly detection M Kloft, U Brefeld, P Düessel, C Gehl, P Laskov Proceedings of the 1st ACM workshop on Workshop on AISec, 71-76, 2008	65	2008
Transductive support vector machines for structured variables A Zien, U Brefeld, T Scheffer Proceedings of the 24th international conference on Machine learning, 1183-1190, 2007	55	2007
Systematic feature evaluation for gene name recognition J Hakenberg, S Bickel, C Plake, U Brefeld, H Zahn, L Faulstich, U Leser, ... BMC bioinformatics 6 (1), 1-11, 2005	49	2005
Spatio-temporal convolution kernels K Knauf, D Memmert, U Brefeld Machine learning 102 (2), 247-273, 2016	47	2016
Hybrid models for future event prediction G Amodeo, R Blanco, U Brefeld Proceedings of the 20th ACM international conference on Information and …, 2011	42	2011
Active and semi-supervised data domain description N Görnitz, M Kloft, U Brefeld Joint European Conference on Machine Learning and Knowledge Discovery in …, 2009	41	2009
Supervised clustering of streaming data for email batch detection P Haider, U Brefeld, T Scheffer Proceedings of the 24th international conference on Machine learning, 345-352, 2007	40	2007
Learning from partially annotated sequences ER Fernandes, U Brefeld Joint European Conference on Machine Learning and Knowledge Discovery in …, 2011	37	2011

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