Marius Kloft

According to our database, Marius Kloft authored at least 115 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Recommendations with minimum exposure guarantees: A post-processing framework.

Ramon Lopes, Rodrigo Alves, Antoine Ledent, Rodrygo L. T. Santos, Marius Kloft

Expert Syst. Appl., February, 2024

On the Challenges and Opportunities in Generative AI.

Laura Manduchi, Kushagra Pandey, Robert Bamler, Ryan Cotterell, Sina Däubener, Sophie Fellenz, Asja Fischer, Thomas Gärtner, Matthias Kirchler, Marius Kloft, Yingzhen Li, Christoph Lippert, Gerard de Melo, Eric T. Nalisnick, Björn Ommer, Rajesh Ranganath, Maja Rudolph, Karen Ullrich, Guy Van den Broeck, Julia E. Vogt, Yixin Wang, Florian Wenzel, Frank Wood, Stephan Mandt, Vincent Fortuin

CoRR, 2024

Reimagining Anomalies: What If Anomalies Were Normal?

Philipp Liznerski, Saurabh Varshneya, Ece Calikus, Sophie Fellenz, Marius Kloft

CoRR, 2024

2023

Orthogonal Inductive Matrix Completion.

Antoine Ledent, Rodrigo Alves, Marius Kloft

IEEE Trans. Neural Networks Learn. Syst., May, 2023

E$^{3}$3Outlier: a Self-Supervised Framework for Unsupervised Deep Outlier Detection.

Siqi Wang, Yijie Zeng, Guang Yu, Zhen Cheng, Xinwang Liu, Sihang Zhou, En Zhu, Marius Kloft, Jianping Yin, Qing Liao

IEEE Trans. Pattern Anal. Mach. Intell., March, 2023

TimeSeAD: Benchmarking Deep Multivariate Time-Series Anomaly Detection.

Dennis Wagner, Tobias Michels, Florian C. F. Schulz, Arjun Nair, Maja Rudolph, Marius Kloft

Trans. Mach. Learn. Res., 2023

Evaluating Dynamic Topic Models.

Charu James, Mayank Nagda, Nooshin Haji Ghassemi, Marius Kloft, Sophie Fellenz

CoRR, 2023

Text Style Transfer Evaluation Using Large Language Models.

Phil Ostheimer, Mayank Nagda, Marius Kloft, Sophie Fellenz

CoRR, 2023

Deep Anomaly Detection on Tennessee Eastman Process Data.

Fabian Hartung, Billy Joe Franks, Tobias Michels, Dennis Wagner, Philipp Liznerski, Steffen Reithermann, Sophie Fellenz, Fabian Jirasek, Maja Rudolph, Daniel Neider, Heike Leitte, Chen Song, Benjamin Klöpper, Stephan Mandt, Michael Bortz, Jakob Burger, Hans Hasse, Marius Kloft

CoRR, 2023

Zero-Shot Anomaly Detection without Foundation Models.

Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, Stephan Mandt

CoRR, 2023

Ordinal Regression for Difficulty Estimation of StepMania Levels.

Billy Joe Franks, Benjamin Dinkelmann, Sophie Fellenz, Marius Kloft

CoRR, 2023

Ordinal Regression for Difficulty Prediction of StepMania Levels.

Billy Joe Franks, Benjamin Dinkelmann, Marius Kloft, Sophie Fellenz

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track, 2023

Zero-Shot Anomaly Detection via Batch Normalization.

Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, Stephan Mandt

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Labeling Neural Representations with Inverse Recognition.

Kirill Bykov, Laura Kopf, Shinichi Nakajima, Marius Kloft, Marina M.-C. Höhne

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Deep Anomaly Detection under Labeling Budget Constraints.

Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Stephan Mandt, Maja Rudolph

Proceedings of the International Conference on Machine Learning, 2023

Training Normalizing Flows from Dependent Data.

Matthias Kirchler, Christoph Lippert, Marius Kloft

Proceedings of the International Conference on Machine Learning, 2023

A Call for Standardization and Validation of Text Style Transfer Evaluation.

Phil Ostheimer, Mayank Kumar Nagda, Marius Kloft, Sophie Fellenz

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

Generalization Bounds for Inductive Matrix Completion in Low-Noise Settings.

Antoine Ledent, Rodrigo Alves, Yunwen Lei, Yann Guermeur, Marius Kloft

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Multiview Subspace Clustering via Co-Training Robust Data Representation.

Jiyuan Liu, Xinwang Liu, Yuexiang Yang, Xifeng Guo, Marius Kloft, Liangzhong He

IEEE Trans. Neural Networks Learn. Syst., 2022

Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images.

Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Klaus-Robert Müller, Marius Kloft

Trans. Mach. Learn. Res., 2022

Unsupervised Anomaly Detection for Auditing Data and Impact of Categorical Encodings.

Ajay Chawda, Stefanie Grimm, Marius Kloft

CoRR, 2022

Detecting Anomalies within Time Series using Local Neural Transformations.

Tim Schneider, Chen Qiu, Marius Kloft, Decky Aspandi-Latif, Steffen Staab, Stephan Mandt, Maja Rudolph

CoRR, 2022

transferGWAS: GWAS of images using deep transfer learning.

Matthias Kirchler, Stefan Konigorski, Matthias Norden, Christian Meltendorf, Marius Kloft, Claudia Schurmann, Christoph Lippert

Bioinform., 2022

Raising the Bar in Graph-level Anomaly Detection.

Chen Qiu, Marius Kloft, Stephan Mandt, Maja Rudolph

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Latent Outlier Exposure for Anomaly Detection with Contaminated Data.

Chen Qiu, Aodong Li, Marius Kloft, Maja Rudolph, Stephan Mandt

Proceedings of the International Conference on Machine Learning, 2022

On the Generalization Analysis of Adversarial Learning.

Waleed Mustafa, Yunwen Lei, Marius Kloft

Proceedings of the International Conference on Machine Learning, 2022

2021

A Unifying Review of Deep and Shallow Anomaly Detection.

Lukas Ruff, Jacob R. Kauffmann, Robert A. Vandermeulen, Grégoire Montavon, Wojciech Samek, Marius Kloft, Thomas G. Dietterich, Klaus-Robert Müller

Proc. IEEE, 2021

Efficient and Effective Regularized Incomplete Multi-View Clustering.

Xinwang Liu, Miaomiao Li, Chang Tang, Jingyuan Xia, Jian Xiong, Li Liu, Marius Kloft, En Zhu

IEEE Trans. Pattern Anal. Mach. Intell., 2021

Trainability for Universal GNNs Through Surgical Randomness.

Billy Joe Franks, Markus Anders, Marius Kloft, Pascal Schweitzer

CoRR, 2021

Explainability Requires Interactivity.

Matthias Kirchler, Martin Graf, Marius Kloft, Christoph Lippert

CoRR, 2021

Explaining Bayesian Neural Networks.

Kirill Bykov, Marina M.-C. Höhne, Adelaida Creosteanu, Klaus-Robert Müller, Frederick Klauschen, Shinichi Nakajima, Marius Kloft

CoRR, 2021

Burst-induced Multi-Armed Bandit for Learning Recommendation.

Rodrigo Alves, Antoine Ledent, Marius Kloft

Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021

Fine-grained Generalization Analysis of Inductive Matrix Completion.

Antoine Ledent, Rodrigo Alves, Yunwen Lei, Marius Kloft

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning Interpretable Concept Groups in CNNs.

Saurabh Varshneya, Antoine Ledent, Robert A. Vandermeulen, Yunwen Lei, Matthias Enders, Damian Borth, Marius Kloft

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Fine-grained Generalization Analysis of Structured Output Prediction.

Waleed Mustafa, Yunwen Lei, Antoine Ledent, Marius Kloft

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Neural Transformation Learning for Deep Anomaly Detection Beyond Images.

Chen Qiu, Timo Pfrommer, Marius Kloft, Stephan Mandt, Maja Rudolph

Proceedings of the 38th International Conference on Machine Learning, 2021

Explainable Deep One-Class Classification.

Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Marius Kloft, Klaus-Robert Müller

Proceedings of the 9th International Conference on Learning Representations, 2021

Model Uncertainty Guides Visual Object Tracking.

Lijun Zhou, Antoine Ledent, Qintao Hu, Ting Liu, Jianlin Zhang, Marius Kloft

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Fine-grained Generalization Analysis of Vector-Valued Learning.

Liang Wu, Antoine Ledent, Yunwen Lei, Marius Kloft

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Norm-Based Generalisation Bounds for Deep Multi-Class Convolutional Neural Networks.

Antoine Ledent, Waleed Mustafa, Yunwen Lei, Marius Kloft

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Multiple Kernel $k$k-Means with Incomplete Kernels.

Xinwang Liu, Xinzhong Zhu, Miaomiao Li, Lei Wang, En Zhu, Tongliang Liu, Marius Kloft, Dinggang Shen, Jianping Yin, Wen Gao

IEEE Trans. Pattern Anal. Mach. Intell., 2020

Input Hessian Regularization of Neural Networks.

Waleed Mustafa, Robert A. Vandermeulen, Marius Kloft

CoRR, 2020

How Much Can I Trust You? - Quantifying Uncertainties in Explaining Neural Networks.

Kirill Bykov, Marina M.-C. Höhne, Klaus-Robert Müller, Shinichi Nakajima, Marius Kloft

CoRR, 2020

Rethinking Assumptions in Deep Anomaly Detection.

Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Klaus-Robert Müller, Marius Kloft

CoRR, 2020

An Empirical Study of the Discreteness Prior in Low-Rank Matrix Completion.

Rodrigo Alves, Antoine Ledent, Renato Assunção, Marius Kloft

Proceedings of the NeurIPS 2020 Workshop on Pre-registration in Machine Learning, 2020

Sharper Generalization Bounds for Pairwise Learning.

Yunwen Lei, Antoine Ledent, Marius Kloft

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Cloze Test Helps: Effective Video Anomaly Detection via Learning to Complete Video Events.

Guang Yu, Siqi Wang, Zhiping Cai, En Zhu, Chuanfu Xu, Jianping Yin, Marius Kloft

Proceedings of the MM '20: The 28th ACM International Conference on Multimedia, 2020

Simple and Effective Prevention of Mode Collapse in Deep One-Class Classification.

Penny Chong, Lukas Ruff, Marius Kloft, Alexander Binder

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Deep Semi-Supervised Anomaly Detection.

Lukas Ruff, Robert A. Vandermeulen, Nico Görnitz, Alexander Binder, Emmanuel Müller, Klaus-Robert Müller, Marius Kloft

Proceedings of the 8th International Conference on Learning Representations, 2020

Two-sample Testing Using Deep Learning.

Matthias Kirchler, Shahryar Khorasani, Marius Kloft, Christoph Lippert

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Data-Dependent Generalization Bounds for Multi-Class Classification.

Yunwen Lei, Ürün Dogan, Ding-Xuan Zhou, Marius Kloft

IEEE Trans. Inf. Theory, 2019

Analyzing the Variance of Policy Gradient Estimators for the Linear-Quadratic Regulator.

James A. Preiss, Sébastien M. R. Arnold, Chen-Yu Wei, Marius Kloft

CoRR, 2019

Improved Generalisation Bounds for Deep Learning Through L^∞ Covering Numbers.

Antoine Ledent, Yunwen Lei, Marius Kloft

CoRR, 2019

Effective End-to-end Unsupervised Outlier Detection via Inlier Priority of Discriminative Network.

Siqi Wang, Yijie Zeng, Xinwang Liu, En Zhu, Jianping Yin, Chuanfu Xu, Marius Kloft

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning a Multimodal Prior Distribution for Generative Adversarial Nets.

Thomas Goerttler, Marius Kloft

Proceedings of the Conference on "Lernen, Wissen, Daten, Analysen", Berlin, Germany, September 30, 2019

Self-Attentive, Multi-Context One-Class Classification for Unsupervised Anomaly Detection on Text.

Lukas Ruff, Yury Zemlyanskiy, Robert A. Vandermeulen, Thomas Schnake, Marius Kloft

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Efficient Gaussian Process Classification Using Pólya-Gamma Data Augmentation.

Florian Wenzel, Théo Galy-Fajou, Christian Donner, Marius Kloft, Manfred Opper

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Support Vector Data Descriptions and k-Means Clustering: One Class?

Nico Görnitz, Luiz Alberto Lima, Klaus-Robert Müller, Marius Kloft, Shinichi Nakajima

IEEE Trans. Neural Networks Learn. Syst., 2018

Local Rademacher Complexity-based Learning Guarantees for Multi-Task Learning.

Niloofar Yousefi, Yunwen Lei, Marius Kloft, Mansooreh Mollaghasemi, Georgios C. Anagnostopoulos

J. Mach. Learn. Res., 2018

Mixed kernel based extreme learning machine for electric load forecasting.

Yanhua Chen, Marius Kloft, Yi Yang, Caihong Li, Lian Li

Neurocomputing, 2018

Extreme Classification (Dagstuhl Seminar 18291).

Samy Bengio, Krzysztof Dembczynski, Thorsten Joachims, Marius Kloft, Manik Varma

Dagstuhl Reports, 2018

Distributed Optimization of All-in-one SVMs for Extreme Classfication.

Marius Kloft

Proceedings of the Companion of the The Web Conference 2018 on The Web Conference 2018, 2018

Image Anomaly Detection with Generative Adversarial Networks.

Lucas Deecke, Robert A. Vandermeulen, Lukas Ruff, Stephan Mandt, Marius Kloft

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Deep One-Class Classification.

Lukas Ruff, Nico Görnitz, Lucas Deecke, Shoaib Ahmed Siddiqui, Robert A. Vandermeulen, Alexander Binder, Emmanuel Müller, Marius Kloft

Proceedings of the 35th International Conference on Machine Learning, 2018

Scalable Generalized Dynamic Topic Models.

Patrick Jähnichen, Florian Wenzel, Marius Kloft, Stephan Mandt

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Sparse probit linear mixed model.

Stephan Mandt, Florian Wenzel, Shinichi Nakajima, John P. Cunningham, Christoph Lippert, Marius Kloft

Mach. Learn., 2017

Generalization Error Bounds for Extreme Multi-class Classification.

Yunwen Lei, Ürün Dogan, Ding-Xuan Zhou, Marius Kloft

CoRR, 2017

Bayesian Nonlinear Support Vector Machines for Big Data.

Florian Wenzel, Théo Galy-Fajou, Matthäus Deutsch, Marius Kloft

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

2016

Feature Importance Measure for Non-linear Learning Algorithms.

Marina M.-C. Vidovic, Nico Görnitz, Klaus-Robert Müller, Marius Kloft

CoRR, 2016

Distributed Optimization of Multi-Class SVMs.

Maximilian Alber, Julian Zimmert, Ürün Dogan, Marius Kloft

CoRR, 2016

Separating Sparse Signals from Correlated Noise in Binary Classification.

Stephan Mandt, Florian Wenzel, Shinichi Nakajima, Christoph Lippert, Marius Kloft

Proceedings of the UAI 2016 Workshop on Causation: Foundation to Application co-located with the 32nd Conference on Uncertainty in Artificial Intelligence (UAI 2016), 2016

Behavior-based tracking of Internet users with semi-supervised learning.

Dominik Herrmann, Matthias Kirchler, Jens Lindemann, Marius Kloft

Proceedings of the 14th Annual Conference on Privacy, Security and Trust, 2016

Huber-Norm Regularization for Linear Prediction Models.

Oleksandr Zadorozhnyi, Gunthard Benecke, Stephan Mandt, Tobias Scheffer, Marius Kloft

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Tracked Without a Trace: Linking Sessions of Users by Unsupervised Learning of Patterns in Their DNS Traffic.

Matthias Kirchler, Dominik Herrmann, Jens Lindemann, Marius Kloft

Proceedings of the 2016 ACM Workshop on Artificial Intelligence and Security, 2016

Localized Multiple Kernel Learning - A Convex Approach.

Yunwen Lei, Alexander Binder, Ürün Dogan, Marius Kloft

Proceedings of The 8th Asian Conference on Machine Learning, 2016

2015

Extracting latent brain states - Towards true labels in cognitive neuroscience experiments.

Anne K. Porbadnigk, Nico Görnitz, Claudia Sannelli, Alexander Binder, Mikio L. Braun, Marius Kloft, Klaus-Robert Müller

NeuroImage, 2015

Probabilistic clustering of time-evolving distance data.

Julia E. Vogt, Marius Kloft, Stefan Stark, Sudhir Raman, Sandhya Prabhakaran, Volker Roth, Gunnar Rätsch

Mach. Learn., 2015

Machine Learning with Interdependent and Non-identically Distributed Data (Dagstuhl Seminar 15152).

Trevor Darrell, Marius Kloft, Massimiliano Pontil, Gunnar Rätsch, Erik Rodner

Dagstuhl Reports, 2015

Framework for Multi-task Multiple Kernel Learning and Applications in Genome Analysis.

Christian Widmer, Marius Kloft, Vipin T. Sreedharan, Gunnar Rätsch

CoRR, 2015

Sparse Estimation in a Correlated Probit Model.

Stephan Mandt, Florian Wenzel, Shinichi Nakajima, John P. Cunningham, Christoph Lippert, Marius Kloft

CoRR, 2015

Opening the Black Box: Revealing Interpretable Sequence Motifs in Kernel-Based Learning Algorithms.

Marina M.-C. Vidovic, Nico Görnitz, Klaus-Robert Müller, Gunnar Rätsch, Marius Kloft

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms.

Yunwen Lei, Ürün Dogan, Alexander Binder, Marius Kloft

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Theory and Algorithms for the Localized Setting of Learning Kernels.

Yunwen Lei, Alexander Binder, Ürün Dogan, Marius Kloft

Proceedings of the 1st Workshop on Feature Extraction: Modern Questions and Challenges, 2015

Hidden Markov Anomaly Detection.

Nico Görnitz, Mikio L. Braun, Marius Kloft

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Efficient Algorithms for Exact Inference in Sequence Labeling SVMs.

Alexander Bauer, Nico Görnitz, Franziska Biegler, Klaus-Robert Müller, Marius Kloft

IEEE Trans. Neural Networks Learn. Syst., 2014

Regularization-Based Multitask Learning With Applications to Genome Biology and Biological Imaging.

Christian Widmer, Marius Kloft, Xinghua Lou, Gunnar Rätsch

Künstliche Intell., 2014

Localized Complexities for Transductive Learning.

Ilya O. Tolstikhin, Gilles Blanchard, Marius Kloft

Proceedings of The 27th Conference on Learning Theory, 2014

When brain and behavior disagree: Tackling systematic label noise in EEG data with machine learning.

Anne K. Porbadnigk, Nico Görnitz, Claudia Sannelli, Alexander Binder, Mikio L. Braun, Marius Kloft, Klaus-Robert Müller

Proceedings of the 2014 International Winter Workshop on Brain-Computer Interface, 2014

Learning and Evaluation in Presence of Non-i.i.d. Label Noise.

Nico Görnitz, Anne Porbadnigk, Alexander Binder, Claudia Sannelli, Mikio L. Braun, Klaus-Robert Müller, Marius Kloft

Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013

Decoding Brain States during Auditory Perception by Supervising Unsupervised Learning.

Anne Porbadnigk, Nico Görnitz, Marius Kloft, Klaus-Robert Müller

J. Comput. Sci. Eng., 2013

Toward Supervised Anomaly Detection.

Nico Görnitz, Marius Kloft, Konrad Rieck, Ulf Brefeld

J. Artif. Intell. Res., 2013

Kernel-Based Machine Learning with Multiple Sources of Information.

Marius Kloft

it Inf. Technol., 2013

Learning Kernels Using Local Rademacher Complexity.

Corinna Cortes, Marius Kloft, Mehryar Mohri

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Multi-task Learning for Computational Biology: Overview and Outlook.

Christian Widmer, Marius Kloft, Gunnar Rätsch

Proceedings of the Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik, 2013

2012

Security analysis of online centroid anomaly detection.

Marius Kloft, Pavel Laskov

J. Mach. Learn. Res., 2012

On the convergence rate of lp-norm multiple kernel learning.

Marius Kloft, Gilles Blanchard

J. Mach. Learn. Res., 2012

Efficient Training of Graph-Regularized Multitask SVMs.

Christian Widmer, Marius Kloft, Nico Görnitz, Gunnar Rätsch

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Early detection of malicious behavior in JavaScript code.

Kristof Schütt, Marius Kloft, Alexander Bikadorov, Konrad Rieck

Proceedings of the 5th ACM Workshop on Security and Artificial Intelligence, 2012

2011

lp-Norm Multiple Kernel Learning.

Marius Kloft

PhD thesis, 2011

<i>l_p</i>-Norm Multiple Kernel Learning.

Marius Kloft, Ulf Brefeld, Sören Sonnenburg, Alexander Zien

J. Mach. Learn. Res., 2011

Insights from Classifying Visual Concepts with Multiple Kernel Learning

Alexander Binder, Shinichi Nakajima, Marius Kloft, Christina Müller, Wojciech Samek, Ulf Brefeld, Klaus-Robert Müller, Motoaki Kawanabe

CoRR, 2011

Transfer Learning with Adaptive Regularizers.

Ulrich Rückert, Marius Kloft

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

The Local Rademacher Complexity of Lp-Norm Multiple Kernel Learning.

Marius Kloft, Gilles Blanchard

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

A new scatter-based multi-class support vector machine.

Robert Jenssen, Marius Kloft, Sören Sonnenburg, Alexander Zien, Klaus-Robert Müller

Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011

Maschinelles Lernen mit multiplen Kernen.

Marius Kloft

Proceedings of the Ausgezeichnete Informatikdissertationen 2011, 2011

The Joint Submission of the TU Berlin and Fraunhofer FIRST (TUBFI) to the ImageCLEF2011 Photo Annotation Task.

Alexander Binder, Wojciech Samek, Marius Kloft, Christina Müller, Klaus-Robert Müller, Motoaki Kawanabe

Proceedings of the CLEF 2011 Labs and Workshop, 2011

2010

Online Anomaly Detection under Adversarial Impact.

Marius Kloft, Pavel Laskov

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Non-Sparse Regularization and Efficient Training with Multiple Kernels

Marius Kloft, Ulf Brefeld, Sören Sonnenburg, Alexander Zien

CoRR, 2010

A Unifying View of Multiple Kernel Learning.

Marius Kloft, Ulrich Rückert, Peter L. Bartlett

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

2009

Feature Selection for Density Level-Sets.

Marius Kloft, Shinichi Nakajima, Ulf Brefeld

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

Active and Semi-supervised Data Domain Description.

Nico Görnitz, Marius Kloft, Ulf Brefeld

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

Efficient and Accurate Lp-Norm Multiple Kernel Learning.

Marius Kloft, Ulf Brefeld, Sören Sonnenburg, Pavel Laskov, Klaus-Robert Müller, Alexander Zien

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

A framework for quantitative security analysis of machine learning.

Pavel Laskov, Marius Kloft

Proceedings of the 2nd ACM Workshop on Security and Artificial Intelligence, 2009

Active learning for network intrusion detection.

Nico Görnitz, Marius Kloft, Konrad Rieck, Ulf Brefeld

Proceedings of the 2nd ACM Workshop on Security and Artificial Intelligence, 2009

2008

Automatic feature selection for anomaly detection.

Marius Kloft, Ulf Brefeld, Patrick Düssel, Christian Gehl, Pavel Laskov

Proceedings of the 1st ACM Workshop on Security and Artificial Intelligence, 2008