Prof. Dr. Marius Kloft

Short Bio

Since 2017 Marius Kloft has been a professor of computer science at TU Kaiserslautern, Germany. Previously, we was an adjunct associate professor of the University of Southern California (09/2018-03/2019), an Emmy-Noether research group leader (2015-), an assistant professor at HU Berlin (2014-2017) and a joint postdoctoral fellow (2012-2014) at the Courant Institute of Mathematical Sciences and Memorial Sloan-Kettering Cancer Center, New York, working with Mehryar Mohri, Corinna Cortes, and Gunnar Rätsch. From 2007-2011, he was a PhD student in the machine learning program of TU Berlin, headed by Klaus-Robert Müller. He was co-advised by Gilles Blanchard and Peter L. Bartlett, whose learning theory group at UC Berkeley he visited from 10/2009 to 10/2010. In 2006, he received a master in mathematics from the University of Marburg with a thesis in algebraic geometry.

Research Interests

Marius Kloft is interested in theory and algorithms of statistical machine learning and its applications, especially in statistical genetics and chemical engineering. He has been working on, e.g., multiple kernel learning, anomaly detection, extreme classification, explainable AI, transfer learning, and adversarial learning for computer security. He co-organized workshops on these topics at NIPS 2010, 2013, 2014, 2017, ICML 2016, and Dagstuhl 2018. His 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). In 2014, he received the Google Most Influential Papers 2013 Award.


Research Group

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Publications of the Group














2008 and before


2017--- Not updated anymore; let's say it's a lot :)
2016 Advisory Board: Basudha Trust. Action Editor: JMLR special issue on Multi Task Learning, Domain Adaptation and Transfer Learning. Program Committee: AAAI, ECAI, ICML, KDML, TFML; Editorial board: Machine Learning. Reviewer: AISTATS, Bioinformatics, COSE, IEEE CYB, CIC, JMLR, MLJ, NEPL, NIPS, Sensors, TDPS, TNNLS, TPAMI. 2015 Advisory Board: Basudha Trust. Action Editor: JMLR. Editorial board: Machine Learning. Workshop Organization: Dagstuhl. Program Committee: FE NIPS WS, IJCAI, KDML. Reviewer: Algorithms, ALT, Bioinformatics, CVIU, COLT, Computation, CVIU, Computers and Security, DFG, EU, ICML, INFFUS, IEEE CYB, IEEE IT, JMLR, Math Rev, MLJ, NEPL, NCAA, NIPS, Sensors, SPM, TNNLS, TPAMI . 2014 Advisory Board: Basudha Trust. Workshop Organization: NIPS. Program Committee: ECCV TASK-CV, ICPR. Reviewer: Bioinformatics, CVIU, ICML, INFFUS, IEEE IP, IEEE IT, INFFUS, IPM, JMLR, Math Rev, MLJ, NEPL, NEUNET, NIPS: PLoS ONE, TKDE, TNNLS, TPAMI, TSMCB. 2013 Workshop Organization: NIPS. Area co-chairing (w G. Rätsch): NIPS. Program Committee: ACML, ECML/PKDD, NCVPRIPG. Reviewer: AISTATS, ALT, 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.

1 This document is the unedited Author's version of a Submitted Work that was subsequently accepted for publication in The Journal of Physical Chemistry Letters, copyright© American Chemical Society after peer review. To access the final edited and published work see

*Contributed equally.
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