Prof. Dr. Marius Kloft




Humboldt University of Berlin
Department of Computer Science
Rudower Chaussee 25
Haus 4, Room 215
12489 Berlin

☎ +49 30 2093 3027

[ Bio | Research | Teaching | Publications | Activities ]

Short Bio

    Since 04/2014 I am a junior professor at the Department of Computer Science of Humboldt University of Berlin. Prior to joining HU Berlin I was a joint postdoctoral fellow at the Courant Institute of Mathematical Sciences and Memorial Sloan-Kettering Cancer Center, New York, working with Mehryar Mohri and Gunnar Rätsch, respectively. From 2007-2011, I was a PhD student in the machine learning program of TU Berlin, headed by Klaus-Robert Müller. I was co-advised by Gilles Blanchard and Peter L. Bartlett, whose learning theory group at UC Berkeley I visited from 10/2009 to 10/2010. In 2006, I received a diploma (MSc equivalent) in mathematics from the University of Marburg with a thesis in algebraic geometry.

Research Interests

    I am interested in statistical machine learning and its applications, in particular, computational biology. For instance, I have been working on several aspects of multiple kernel learning: (non-sparse) regularization strategies, generalization bounds, unified framework, and novelty detection. I have co-organized workshops on new directions in multiple kernel learning and multi-task and transfer learning at NIPS 2010 and 2013, respectively. My dissertation on Lp-norm multiple kernel learning was nominated by TU Berlin for the Doctoral Dissertation Award of the German Chapter of the ACM (GI).

News


Teaching


Publications

    2014

    2013

  • C. Cortes, M. Kloft, M. Mohri. Learning Kernels Using Local Rademacher Complexity.
    Advances in Neural Information Processing Systems (NIPS) 26: 2760-2768, 2013.
    Spotlight paper (52 spotlights out of 1420 submissions). Google Most Influential Papers 2013 Award.

    2012

    2011

  • M. Kloft. Lp-Norm Multiple Kernel Learning.
    Dissertation, Berlin Institute of Technology (TU Berlin), Oct 2011.
    Finalist - Doctoral Dissertation Award of the German Chapter of the ACM.

    2010

    2009

  • A. Binder, M. Kawanabe, M. Kloft, and S. Nakajima. Enhancing Image Annotation with Primitive Color Histograms via Non-sparse Multiple Kernel Learning. NIPS Workshop on Understanding Multiple Kernel Learning Methods, 2009.
  • M. Kloft, U. Brefeld, S. Sonnenburg, A. Zien, P. Laskov, and K.-R. Müller. Learning Non-sparse Kernel Mixtures.
    Proceedings of the PASCAL2 Workshop on Sparsity in Machine Learning and Statistics, 2009.

    2008 and before

  • M. Kloft, U. Brefeld, P. Laskov, and S. Sonnenburg. Non-sparse Multiple Kernel Learning.
    Proceedings of the NIPS Workshop on Kernel Learning: Automatic Selection of Optimal Kernels, 2008.


Activities


2013
Workshop Organization: NIPS: Area co-chairing (w G. Rätsch): NIPS: Program Committee: ACML, ECML/PKDD, NCVPRIPG. Reviewer: AISTATS, Bioinformatics, Biosystems, EJS, ICML, IJA, IEEE IT, IJITDM, JMLR, Math Rev, MLCB, NEPL, NEUCOM, NIPS, PloS Comp Bio, PLoS ONE, SPM, TKDE, TNNLS, TPAMI, TSMCB.
2012
Program Committee: ECML/PKDD. ICPR; Reviewer: COLT, DKE, EJS, ICVGIP, JMLR, JCST, NEPL, NEUCOM, NEUNET, NIPS, OPT2012, PR, SMCB, SPM, TNNLS, TPAMI.
2011
Program Committee: IJCAI; Reviewer: COLT, DAGM, ICML, JCST, JMLR, KAIS, MLJ, NEPL, NIPS, TNN, TPAMI, ZUSC.
2010
Workshop Organization: NIPS; Program Committee: AISEC, ECML/PKDD, ICPR; Reviewer: BInf, CSDA, ICML, JMLR, MLJ, NEPL, NIPS, TNN, TPAMI.
2009
Program Committee: AISEC; Reviewer: TPAMI, TNN, PR, ECML/PKDD, NIPS, ICML, AISTATS.
2008
Reviewer: TPAMI, NEUCOM, AAAI, PAKDD, ECML/PKDD, NIPS.
2007
Reviewer: NIPS, PAKDD.


Acknowledgements / Collaborators





*The original publication is available at http://www.acm.org
**The original publication is available at http://www.springerlink.com
***The original publication is available at http://ieeexplore.ieee.org
****The original publication is available at http://journals.cambridge.org
*****The original publication is available at http://www.plosone.org