Marius Kloft - RankMe

175 papers A* 28A 6B 2C 2Journal 101Unranked 34

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	Continual Neural Topic Model. EACL (Volume 1: Long Papers) Charu Karakkaparambil James, Waleed Mustafa, Marcio Monteiro, Marius Kloft, Sophie Fellenz
2026	J	`jnl`	Credal Concept Bottleneck Models: Structural Separation of Epistemic and Aleatoric Uncertainty. CoRR Tanmoy Mukherjee, Marius Kloft, Pierre Marquis, Zied Bouraoui
2026	J	`jnl`	Optimization, Generalization and Differential Privacy Bounds for Gradient Descent on Kolmogorov-Arnold Networks. CoRR Puyu Wang, Junyu Zhou, Philipp Liznerski, Marius Kloft
2026	A*	`conf`	Reimagining Anomalies: What If Anomalies Were Normal? AAAI Philipp Liznerski, Saurabh Varshneya, Ece Calikus, Puyu Wang, Alexander Bartscher, Sebastian Josef Vollmer, Sophie Fellenz, Marius Kloft
2026	A*	`conf`	TORA: Train Once, Realign Anytime for Offline Multi-Objective Reinforcement Learning. AAAI Weichen Li, Waleed Mustafa, Marcio Monteiro, Puyu Wang, Marius Kloft, Sophie Fellenz
2025	J	`jnl`	Challenging Assumptions in Learning Generic Text Style Embeddings. CoRR Phil Ostheimer, Marius Kloft, Sophie Fellenz
2025	J	`jnl`	Continual Neural Topic Model. CoRR Charu Karakkaparambil James, Waleed Mustafa, Marius Kloft, Sophie Fellenz
2025	J	`jnl`	DiffStyleTS: Diffusion Model for Style Transfer in Time Series. CoRR Mayank Nagda, Phil Ostheimer, Justus Arweiler, Indra Jungjohann, Jennifer Werner, Dennis Wagner, Aparna Muraleedharan, Pouya Jafari, Jochen Schmid, Fabian Jirasek, Jakob Burger, Michael Bortz, Hans Hasse, Stephan Mandt, Marius Kloft, Sophie Fellenz
2025	J	`jnl`	Explaining Bayesian Neural Networks. Trans. Mach. Learn. Res. Kirill Bykov, Marina M.-C. Höhne, Adelaida Creosteanu, Klaus-Robert Müller, Frederick Klauschen, Shinichi Nakajima, Marius Kloft
2025	J	`jnl`	Formally Exploring Time-Series Anomaly Detection Evaluation Metrics. CoRR Dennis Wagner, Arjun Nair, Billy Joe Franks, Justus Arweiler, Aparna Muraleedharan, Indra Jungjohann, Fabian Hartung, Mayank C. Ahuja, Andriy Balinskyy, Saurabh Varshneya, Nabeel Hussain Syed, Mayank Nagda, Philipp Liznerski, Steffen Reithermann, Maja Rudolph, Sebastian J. Vollmer, Ralf Schulz, Torsten Katz, Stephan Mandt, Michael Bortz, Heike Leitte, Daniel Neider, Jakob Burger, Fabian Jirasek, Hans Hasse, Sophie Fellenz, Marius Kloft
2025	J	`jnl`	Multi-level Supervised Contrastive Learning. CoRR Naghmeh Ghanooni, Barbod Pajoum, Harshit Rawal, Sophie Fellenz, Vo Nguyen Le Duy, Marius Kloft
2025	J	`jnl`	On the Challenges and Opportunities in Generative AI. Trans. Mach. Learn. Res. Laura Manduchi, Clara Meister, 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
2025	B	`conf`	Optimal Utility Bounds for Differentially Private Gradient Descent in Three-Layer Neural Networks. DSAA Puyu Wang, Yunwen Lei, Marius Kloft, Yiming Ying
2025	J	`jnl`	PIANO: Physics Informed Autoregressive Network. CoRR Mayank Nagda, Jephte Abijuru, Phil Ostheimer, Marius Kloft, Sophie Fellenz
2025	J	`jnl`	Self-Supervised Anomaly Detection With Neural Transformations. IEEE Trans. Pattern Anal. Mach. Intell. Chen Qiu, Marius Kloft, Stephan Mandt, Maja Rudolph
2025	J	`jnl`	Sparse Data Generation Using Diffusion Models. CoRR Phil Ostheimer, Mayank Nagda, Marius Kloft, Sophie Fellenz
2025	J	`jnl`	Towards Graph Foundation Models: A Study on the Generalization of Positional and Structural Encodings. Trans. Mach. Learn. Res. Billy Joe Franks, Moshe Eliasof, Semih Cantürk, Guy Wolf, Carola-Bibiane Schönlieb, Sophie Fellenz, Marius Kloft
2024	J	`jnl`	AI-based Anomaly Detection for Clinical-Grade Histopathological Diagnostics. CoRR Jonas Dippel, Niklas Prenißl, Julius Hense, Philipp Liznerski, Tobias Winterhoff, Simon Schallenberg, Marius Kloft, Oliver Buchstab, David Horst, Maximilian Alber, Lukas Ruff, Klaus-Robert Müller, Frederick Klauschen
2024	J	`jnl`	Anomaly Detection of Tabular Data Using LLMs. CoRR Aodong Li, Yunhan Zhao, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, Stephan Mandt
2024	—	`conf`	Characterizing Text Datasets with Psycholinguistic Features. EMNLP (Findings) Marcio Monteiro, Charu Karakkaparambil James, Marius Kloft, Sophie Fellenz
2024	J	`jnl`	Comgra: A Tool for Analyzing and Debugging Neural Networks. CoRR Florian Dietz, Sophie Fellenz, Dietrich Klakow, Marius Kloft
2024	—	`conf`	Evaluating Dynamic Topic Models. ACL (1) Charu James, Mayank Nagda, Nooshin Haji Ghassemi, Marius Kloft, Sophie Fellenz
2024	J	`jnl`	Generalization Bounds with Logarithmic Negative-Sample Dependence for Adversarial Contrastive Learning. Trans. Mach. Learn. Res. Naghmeh Ghanooni, Waleed Mustafa, Yunwen Lei, Anthony Widjaja Lin, Marius Kloft
2024	A*	`conf`	Interpretable Tensor Fusion. IJCAI Saurabh Varshneya, Antoine Ledent, Philipp Liznerski, Andriy Balinskyy, Purvanshi Mehta, Waleed Mustafa, Marius Kloft
2024	J	`jnl`	Interpretable Tensor Fusion. CoRR Saurabh Varshneya, Antoine Ledent, Philipp Liznerski, Andriy Balinskyy, Purvanshi Mehta, Waleed Mustafa, Marius Kloft
2024	A	`conf`	Non-vacuous Generalization Bounds for Adversarial Risk in Stochastic Neural Networks. AISTATS Waleed Mustafa, Philipp Liznerski, Antoine Ledent, Dennis Wagner, Puyu Wang, Marius Kloft
2024	J	`jnl`	On the Challenges and Opportunities in Generative AI. CoRR 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
2024	J	`jnl`	Recommendations with minimum exposure guarantees: A post-processing framework. Expert Syst. Appl. Ramon Lopes, Rodrigo Alves, Antoine Ledent, Rodrygo L. T. Santos, Marius Kloft
2024	J	`jnl`	Reimagining Anomalies: What If Anomalies Were Normal? CoRR Philipp Liznerski, Saurabh Varshneya, Ece Calikus, Sophie Fellenz, Marius Kloft
2024	J	`jnl`	SetPINNs: Set-based Physics-informed Neural Networks. CoRR Mayank Nagda, Phil Ostheimer, Thomas Specht, Frank Rhein, Fabian Jirasek, Marius Kloft, Sophie Fellenz
2024	—	`conf`	Text Style Transfer Evaluation Using Large Language Models. LREC/COLING Phil Sidney Ostheimer, Mayank Kumar Nagda, Marius Kloft, Sophie Fellenz
2024	J	`jnl`	Towards Graph Foundation Models: A Study on the Generalization of Positional and Structural Encodings. CoRR Billy Joe Franks, Moshe Eliasof, Semih Cantürk, Guy Wolf, Carola-Bibiane Schönlieb, Sophie Fellenz, Marius Kloft
2024	J	`jnl`	Uncertainty-Adjusted Recommendation via Matrix Factorization With Weighted Losses. IEEE Trans. Neural Networks Learn. Syst. Rodrigo Alves, Antoine Ledent, Marius Kloft
2024	A*	`conf`	Unraveling the Dynamics of Stable and Curious Audiences in Web Systems. WWW Rodrigo Alves, Antoine Ledent, Renato Assunção, Pedro O. S. Vaz de Melo, Marius Kloft
2023	—	`conf`	A Call for Standardization and Validation of Text Style Transfer Evaluation. ACL (Findings) Phil Ostheimer, Mayank Kumar Nagda, Marius Kloft, Sophie Fellenz
2023	J	`jnl`	A Call for Standardization and Validation of Text Style Transfer Evaluation. CoRR Phil Ostheimer, Mayank Nagda, Marius Kloft, Sophie Fellenz
2023	J	`jnl`	A Systematic Approach to Universal Random Features in Graph Neural Networks. Trans. Mach. Learn. Res. Billy Joe Franks, Markus Anders, Marius Kloft, Pascal Schweitzer
2023	J	`jnl`	Deep Anomaly Detection on Tennessee Eastman Process Data. CoRR 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
2023	A*	`conf`	Deep Anomaly Detection under Labeling Budget Constraints. ICML Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Stephan Mandt, Maja Rudolph
2023	J	`jnl`	Deep Anomaly Detection under Labeling Budget Constraints. CoRR Aodong Li, Chen Qiu, Padhraic Smyth, Marius Kloft, Stephan Mandt, Maja Rudolph
2023	J	`jnl`	E$^{3}$3Outlier: a Self-Supervised Framework for Unsupervised Deep Outlier Detection. IEEE Trans. Pattern Anal. Mach. Intell. Siqi Wang, Yijie Zeng, Guang Yu, Zhen Cheng, Xinwang Liu, Sihang Zhou, En Zhu, Marius Kloft, Jianping Yin, Qing Liao
2023	J	`jnl`	Evaluating Dynamic Topic Models. CoRR Charu James, Mayank Nagda, Nooshin Haji Ghassemi, Marius Kloft, Sophie Fellenz
2023	A*	`conf`	Generalization Bounds for Inductive Matrix Completion in Low-Noise Settings. AAAI Antoine Ledent, Rodrigo Alves, Yunwen Lei, Yann Guermeur, Marius Kloft
2023	A*	`conf`	Labeling Neural Representations with Inverse Recognition. NeurIPS Kirill Bykov, Laura Kopf, Shinichi Nakajima, Marius Kloft, Marina M.-C. Höhne
2023	J	`jnl`	Labeling Neural Representations with Inverse Recognition. CoRR Kirill Bykov, Laura Kopf, Shinichi Nakajima, Marius Kloft, Marina M.-C. Höhne
2023	J	`jnl`	Ordinal Regression for Difficulty Estimation of StepMania Levels. CoRR Billy Joe Franks, Benjamin Dinkelmann, Sophie Fellenz, Marius Kloft
2023	—	`conf`	Ordinal Regression for Difficulty Prediction of StepMania Levels. ECML/PKDD (6) Billy Joe Franks, Benjamin Dinkelmann, Marius Kloft, Sophie Fellenz
2023	J	`jnl`	Orthogonal Inductive Matrix Completion. IEEE Trans. Neural Networks Learn. Syst. Antoine Ledent, Rodrigo Alves, Marius Kloft
2023	J	`jnl`	Text Style Transfer Evaluation Using Large Language Models. CoRR Phil Ostheimer, Mayank Nagda, Marius Kloft, Sophie Fellenz
2023	J	`jnl`	TimeSeAD: Benchmarking Deep Multivariate Time-Series Anomaly Detection. Trans. Mach. Learn. Res. Dennis Wagner, Tobias Michels, Florian C. F. Schulz, Arjun Nair, Maja Rudolph, Marius Kloft
2023	A*	`conf`	Training Normalizing Flows from Dependent Data. ICML Matthias Kirchler, Christoph Lippert, Marius Kloft
2023	A*	`conf`	Zero-Shot Anomaly Detection via Batch Normalization. NeurIPS Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, Stephan Mandt
2023	J	`jnl`	Zero-Shot Anomaly Detection without Foundation Models. CoRR Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, Stephan Mandt
2022	J	`jnl`	Detecting Anomalies within Time Series using Local Neural Transformations. CoRR Tim Schneider, Chen Qiu, Marius Kloft, Decky Aspandi-Latif, Steffen Staab, Stephan Mandt, Maja Rudolph
2022	J	`jnl`	Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images. CoRR Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Klaus-Robert Müller, Marius Kloft
2022	J	`jnl`	Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images. Trans. Mach. Learn. Res. Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Klaus-Robert Müller, Marius Kloft
2022	J	`jnl`	Generalization Bounds for Inductive Matrix Completion in Low-noise Settings. CoRR Antoine Ledent, Rodrigo Alves, Yunwen Lei, Yann Guermeur, Marius Kloft
2022	A*	`conf`	Latent Outlier Exposure for Anomaly Detection with Contaminated Data. ICML Chen Qiu, Aodong Li, Marius Kloft, Maja Rudolph, Stephan Mandt
2022	J	`jnl`	Latent Outlier Exposure for Anomaly Detection with Contaminated Data. CoRR Chen Qiu, Aodong Li, Marius Kloft, Maja Rudolph, Stephan Mandt
2022	J	`jnl`	Multiview Subspace Clustering via Co-Training Robust Data Representation. IEEE Trans. Neural Networks Learn. Syst. Jiyuan Liu, Xinwang Liu, Yuexiang Yang, Xifeng Guo, Marius Kloft, Liangzhong He
2022	A*	`conf`	On the Generalization Analysis of Adversarial Learning. ICML Waleed Mustafa, Yunwen Lei, Marius Kloft
2022	A*	`conf`	Raising the Bar in Graph-level Anomaly Detection. IJCAI Chen Qiu, Marius Kloft, Stephan Mandt, Maja Rudolph
2022	J	`jnl`	Raising the Bar in Graph-level Anomaly Detection. CoRR Chen Qiu, Marius Kloft, Stephan Mandt, Maja Rudolph
2022	J	`jnl`	Training Normalizing Flows from Dependent Data. CoRR Matthias Kirchler, Christoph Lippert, Marius Kloft
2022	J	`jnl`	Unsupervised Anomaly Detection for Auditing Data and Impact of Categorical Encodings. CoRR Ajay Chawda, Stefanie Grimm, Marius Kloft
2022	J	`jnl`	transferGWAS: GWAS of images using deep transfer learning. Bioinform. Matthias Kirchler, Stefan Konigorski, Matthias Norden, Christian Meltendorf, Marius Kloft, Claudia Schurmann, Christoph Lippert
2021	J	`jnl`	A Unifying Review of Deep and Shallow Anomaly Detection. Proc. IEEE Lukas Ruff, Jacob R. Kauffmann, Robert A. Vandermeulen, Grégoire Montavon, Wojciech Samek, Marius Kloft, Thomas G. Dietterich, Klaus-Robert Müller
2021	A	`conf`	Burst-induced Multi-Armed Bandit for Learning Recommendation. RecSys Rodrigo Alves, Antoine Ledent, Marius Kloft
2021	J	`jnl`	Efficient and Effective Regularized Incomplete Multi-View Clustering. IEEE Trans. Pattern Anal. Mach. Intell. Xinwang Liu, Miaomiao Li, Chang Tang, Jingyuan Xia, Jian Xiong, Li Liu, Marius Kloft, En Zhu
2021	J	`jnl`	Explainability Requires Interactivity. CoRR Matthias Kirchler, Martin Graf, Marius Kloft, Christoph Lippert
2021	A*	`conf`	Explainable Deep One-Class Classification. ICLR Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Marius Kloft, Klaus-Robert Müller
2021	J	`jnl`	Explaining Bayesian Neural Networks. CoRR Kirill Bykov, Marina M.-C. Höhne, Adelaida Creosteanu, Klaus-Robert Müller, Frederick Klauschen, Shinichi Nakajima, Marius Kloft
2021	A*	`conf`	Fine-grained Generalization Analysis of Inductive Matrix Completion. NeurIPS Antoine Ledent, Rodrigo Alves, Yunwen Lei, Marius Kloft
2021	A*	`conf`	Fine-grained Generalization Analysis of Structured Output Prediction. IJCAI Waleed Mustafa, Yunwen Lei, Antoine Ledent, Marius Kloft
2021	J	`jnl`	Fine-grained Generalization Analysis of Structured Output Prediction. CoRR Waleed Mustafa, Yunwen Lei, Antoine Ledent, Marius Kloft
2021	A*	`conf`	Fine-grained Generalization Analysis of Vector-Valued Learning. AAAI Liang Wu, Antoine Ledent, Yunwen Lei, Marius Kloft
2021	J	`jnl`	Fine-grained Generalization Analysis of Vector-valued Learning. CoRR Liang Wu, Antoine Ledent, Yunwen Lei, Marius Kloft
2021	A*	`conf`	Learning Interpretable Concept Groups in CNNs. IJCAI Saurabh Varshneya, Antoine Ledent, Robert A. Vandermeulen, Yunwen Lei, Matthias Enders, Damian Borth, Marius Kloft
2021	J	`jnl`	Learning Interpretable Concept Groups in CNNs. CoRR Saurabh Varshneya, Antoine Ledent, Robert A. Vandermeulen, Yunwen Lei, Matthias Enders, Damian Borth, Marius Kloft
2021	A*	`conf`	Model Uncertainty Guides Visual Object Tracking. AAAI Lijun Zhou, Antoine Ledent, Qintao Hu, Ting Liu, Jianlin Zhang, Marius Kloft
2021	A*	`conf`	Neural Transformation Learning for Deep Anomaly Detection Beyond Images. ICML Chen Qiu, Timo Pfrommer, Marius Kloft, Stephan Mandt, Maja Rudolph
2021	J	`jnl`	Neural Transformation Learning for Deep Anomaly Detection Beyond Images. CoRR Chen Qiu, Timo Pfrommer, Marius Kloft, Stephan Mandt, Maja Rudolph
2021	A*	`conf`	Norm-Based Generalisation Bounds for Deep Multi-Class Convolutional Neural Networks. AAAI Antoine Ledent, Waleed Mustafa, Yunwen Lei, Marius Kloft
2021	J	`jnl`	Trainability for Universal GNNs Through Surgical Randomness. CoRR Billy Joe Franks, Markus Anders, Marius Kloft, Pascal Schweitzer
2020	J	`jnl`	A Unifying Review of Deep and Shallow Anomaly Detection. CoRR Lukas Ruff, Jacob R. Kauffmann, Robert A. Vandermeulen, Grégoire Montavon, Wojciech Samek, Marius Kloft, Thomas G. Dietterich, Klaus-Robert Müller
2020	—	`conf`	An Empirical Study of the Discreteness Prior in Low-Rank Matrix Completion. Preregister@NeurIPS Rodrigo Alves, Antoine Ledent, Renato Assunção, Marius Kloft
2020	A*	`conf`	Cloze Test Helps: Effective Video Anomaly Detection via Learning to Complete Video Events. ACM Multimedia Guang Yu, Siqi Wang, Zhiping Cai, En Zhu, Chuanfu Xu, Jianping Yin, Marius Kloft
2020	J	`jnl`	Cloze Test Helps: Effective Video Anomaly Detection via Learning to Complete Video Events. CoRR Guang Yu, Siqi Wang, Zhiping Cai, En Zhu, Chuanfu Xu, Jianping Yin, Marius Kloft
2020	A*	`conf`	Deep Semi-Supervised Anomaly Detection. ICLR Lukas Ruff, Robert A. Vandermeulen, Nico Görnitz, Alexander Binder, Emmanuel Müller, Klaus-Robert Müller, Marius Kloft
2020	J	`jnl`	Explainable Deep One-Class Classification. CoRR Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Marius Kloft, Klaus-Robert Müller
2020	J	`jnl`	How Much Can I Trust You? - Quantifying Uncertainties in Explaining Neural Networks. CoRR Kirill Bykov, Marina M.-C. Höhne, Klaus-Robert Müller, Shinichi Nakajima, Marius Kloft
2020	J	`jnl`	Input Hessian Regularization of Neural Networks. CoRR Waleed Mustafa, Robert A. Vandermeulen, Marius Kloft
2020	J	`jnl`	Multiple Kernel $k$k-Means with Incomplete Kernels. IEEE Trans. Pattern Anal. Mach. Intell. Xinwang Liu, Xinzhong Zhu, Miaomiao Li, Lei Wang, En Zhu, Tongliang Liu, Marius Kloft, Dinggang Shen, Jianping Yin, Wen Gao
2020	J	`jnl`	Orthogonal Inductive Matrix Completion. CoRR Antoine Ledent, Rodrigo Alves, Marius Kloft
2020	J	`jnl`	Rethinking Assumptions in Deep Anomaly Detection. CoRR Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Klaus-Robert Müller, Marius Kloft
2020	A*	`conf`	Sharper Generalization Bounds for Pairwise Learning. NeurIPS Yunwen Lei, Antoine Ledent, Marius Kloft
2020	B	`conf`	Simple and Effective Prevention of Mode Collapse in Deep One-Class Classification. IJCNN Penny Chong, Lukas Ruff, Marius Kloft, Alexander Binder
2020	J	`jnl`	Simple and Effective Prevention of Mode Collapse in Deep One-Class Classification. CoRR Penny Chong, Lukas Ruff, Marius Kloft, Alexander Binder
2020	A	`conf`	Two-sample Testing Using Deep Learning. AISTATS Matthias Kirchler, Shahryar Khorasani, Marius Kloft, Christoph Lippert
2019	J	`jnl`	Analyzing the Variance of Policy Gradient Estimators for the Linear-Quadratic Regulator. CoRR James A. Preiss, Sébastien M. R. Arnold, Chen-Yu Wei, Marius Kloft
2019	J	`jnl`	Data-Dependent Generalization Bounds for Multi-Class Classification. IEEE Trans. Inf. Theory Yunwen Lei, Ürün Dogan, Ding-Xuan Zhou, Marius Kloft
2019	J	`jnl`	Deep Semi-Supervised Anomaly Detection. CoRR Lukas Ruff, Robert A. Vandermeulen, Nico Görnitz, Alexander Binder, Emmanuel Müller, Klaus-Robert Müller, Marius Kloft
2019	A*	`conf`	Effective End-to-end Unsupervised Outlier Detection via Inlier Priority of Discriminative Network. NeurIPS Siqi Wang, Yijie Zeng, Xinwang Liu, En Zhu, Jianping Yin, Chuanfu Xu, Marius Kloft
2019	A*	`conf`	Efficient Gaussian Process Classification Using Pólya-Gamma Data Augmentation. AAAI Florian Wenzel, Théo Galy-Fajou, Christian Donner, Marius Kloft, Manfred Opper
2019	J	`jnl`	Improved Generalisation Bounds for Deep Learning Through L CoRR Antoine Ledent, Yunwen Lei, Marius Kloft
2019	—	`conf`	Learning a Multimodal Prior Distribution for Generative Adversarial Nets. LWDA Thomas Goerttler, Marius Kloft
2019	—	`conf`	Self-Attentive, Multi-Context One-Class Classification for Unsupervised Anomaly Detection on Text. ACL (1) Lukas Ruff, Yury Zemlyanskiy, Robert A. Vandermeulen, Thomas Schnake, Marius Kloft
2019	J	`jnl`	Two-sample Testing Using Deep Learning. CoRR Matthias Kirchler, Shahryar Khorasani, Marius Kloft, Christoph Lippert
2018	A*	`conf`	Deep One-Class Classification. ICML Lukas Ruff, Nico Görnitz, Lucas Deecke, Shoaib Ahmed Siddiqui, Robert A. Vandermeulen, Alexander Binder, Emmanuel Müller, Marius Kloft
2018	—	`conf`	Distributed Optimization of All-in-one SVMs for Extreme Classfication. WWW (Companion Volume) Marius Kloft
2018	J	`jnl`	Efficient Gaussian Process Classification Using Polya-Gamma Data Augmentation. CoRR Florian Wenzel, Théo Galy-Fajou, Christian Donner, Marius Kloft, Manfred Opper
2018	J	`jnl`	Extreme Classification (Dagstuhl Seminar 18291). Dagstuhl Reports Samy Bengio, Krzysztof Dembczynski, Thorsten Joachims, Marius Kloft, Manik Varma
2018	—	`conf`	Image Anomaly Detection with Generative Adversarial Networks. ECML/PKDD (1) Lucas Deecke, Robert A. Vandermeulen, Lukas Ruff, Stephan Mandt, Marius Kloft
2018	J	`jnl`	Local Rademacher Complexity-based Learning Guarantees for Multi-Task Learning. J. Mach. Learn. Res. Niloofar Yousefi, Yunwen Lei, Marius Kloft, Mansooreh Mollaghasemi, Georgios C. Anagnostopoulos
2018	J	`jnl`	Mixed kernel based extreme learning machine for electric load forecasting. Neurocomputing Yanhua Chen, Marius Kloft, Yi Yang, Caihong Li, Lian Li
2018	A	`conf`	Scalable Generalized Dynamic Topic Models. AISTATS Patrick Jähnichen, Florian Wenzel, Marius Kloft, Stephan Mandt
2018	J	`jnl`	Scalable Generalized Dynamic Topic Models. CoRR Patrick Jähnichen, Florian Wenzel, Marius Kloft, Stephan Mandt
2018	J	`jnl`	Support Vector Data Descriptions and k-Means Clustering: One Class? IEEE Trans. Neural Networks Learn. Syst. Nico Görnitz, Luiz Alberto Lima, Klaus-Robert Müller, Marius Kloft, Shinichi Nakajima
2017	—	`conf`	Bayesian Nonlinear Support Vector Machines for Big Data. ECML/PKDD (1) Florian Wenzel, Théo Galy-Fajou, Matthäus Deutsch, Marius Kloft
2017	J	`jnl`	Bayesian Nonlinear Support Vector Machines for Big Data. CoRR Florian Wenzel, Théo Galy-Fajou, Matthäus Deutsch, Marius Kloft
2017	J	`jnl`	Generalization Error Bounds for Extreme Multi-class Classification. CoRR Yunwen Lei, Ürün Dogan, Ding-Xuan Zhou, Marius Kloft
2017	J	`jnl`	Sparse probit linear mixed model. Mach. Learn. Stephan Mandt, Florian Wenzel, Shinichi Nakajima, John P. Cunningham, Christoph Lippert, Marius Kloft
2016	C	`conf`	Behavior-based tracking of Internet users with semi-supervised learning. PST Dominik Herrmann, Matthias Kirchler, Jens Lindemann, Marius Kloft
2016	J	`jnl`	Distributed Optimization of Multi-Class SVMs. CoRR Maximilian Alber, Julian Zimmert, Ürün Dogan, Marius Kloft
2016	J	`jnl`	Feature Importance Measure for Non-linear Learning Algorithms. CoRR Marina M.-C. Vidovic, Nico Görnitz, Klaus-Robert Müller, Marius Kloft
2016	—	`conf`	Huber-Norm Regularization for Linear Prediction Models. ECML/PKDD (1) Oleksandr Zadorozhnyi, Gunthard Benecke, Stephan Mandt, Tobias Scheffer, Marius Kloft
2016	J	`jnl`	Local Rademacher Complexity-based Learning Guarantees for Multi-Task Learning. CoRR Niloofar Yousefi, Yunwen Lei, Marius Kloft, Mansooreh Mollaghasemi, Georgios C. Anagnostopoulos
2016	C	`conf`	Localized Multiple Kernel Learning - A Convex Approach. ACML Yunwen Lei, Alexander Binder, Ürün Dogan, Marius Kloft
2016	—	`conf`	Separating Sparse Signals from Correlated Noise in Binary Classification. CFA@UAI Stephan Mandt, Florian Wenzel, Shinichi Nakajima, Christoph Lippert, Marius Kloft
2016	—	`conf`	Tracked Without a Trace: Linking Sessions of Users by Unsupervised Learning of Patterns in Their DNS Traffic. AISec@CCS Matthias Kirchler, Dominik Herrmann, Jens Lindemann, Marius Kloft
2015	J	`jnl`	Extracting latent brain states - Towards true labels in cognitive neuroscience experiments. NeuroImage Anne K. Porbadnigk, Nico Görnitz, Claudia Sannelli, Alexander Binder, Mikio L. Braun, Marius Kloft, Klaus-Robert Müller
2015	J	`jnl`	Framework for Multi-task Multiple Kernel Learning and Applications in Genome Analysis. CoRR Christian Widmer, Marius Kloft, Vipin T. Sreedharan, Gunnar Rätsch
2015	A*	`conf`	Hidden Markov Anomaly Detection. ICML Nico Görnitz, Mikio L. Braun, Marius Kloft
2015	J	`jnl`	Localized Multiple Kernel Learning - A Convex Approach. CoRR Yunwen Lei, Alexander Binder, Ürün Dogan, Marius Kloft
2015	J	`jnl`	Machine Learning with Interdependent and Non-identically Distributed Data (Dagstuhl Seminar 15152). Dagstuhl Reports Trevor Darrell, Marius Kloft, Massimiliano Pontil, Gunnar Rätsch, Erik Rodner
2015	—	`conf`	Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms. NIPS Yunwen Lei, Ürün Dogan, Alexander Binder, Marius Kloft
2015	J	`jnl`	Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms. CoRR Yunwen Lei, Ürün Dogan, Alexander Binder, Marius Kloft
2015	—	`conf`	Opening the Black Box: Revealing Interpretable Sequence Motifs in Kernel-Based Learning Algorithms. ECML/PKDD (2) Marina M.-C. Vidovic, Nico Görnitz, Klaus-Robert Müller, Gunnar Rätsch, Marius Kloft
2015	J	`jnl`	Probabilistic Clustering of Time-Evolving Distance Data. CoRR Julia E. Vogt, Marius Kloft, Stefan Stark, Sudhir Raman, Sandhya Prabhakaran, Volker Roth, Gunnar Rätsch
2015	J	`jnl`	Probabilistic clustering of time-evolving distance data. Mach. Learn. Julia E. Vogt, Marius Kloft, Stefan Stark, Sudhir Raman, Sandhya Prabhakaran, Volker Roth, Gunnar Rätsch
2015	J	`jnl`	Sparse Estimation in a Correlated Probit Model. CoRR Stephan Mandt, Florian Wenzel, Shinichi Nakajima, John P. Cunningham, Christoph Lippert, Marius Kloft
2015	—	`conf`	Theory and Algorithms for the Localized Setting of Learning Kernels. FE@NIPS Yunwen Lei, Alexander Binder, Ürün Dogan, Marius Kloft
2014	J	`jnl`	Efficient Algorithms for Exact Inference in Sequence Labeling SVMs. IEEE Trans. Neural Networks Learn. Syst. Alexander Bauer, Nico Görnitz, Franziska Biegler, Klaus-Robert Müller, Marius Kloft
2014	A	`conf`	Learning and Evaluation in Presence of Non-i.i.d. Label Noise. AISTATS Nico Görnitz, Anne Porbadnigk, Alexander Binder, Claudia Sannelli, Mikio L. Braun, Klaus-Robert Müller, Marius Kloft
2014	A*	`conf`	Localized Complexities for Transductive Learning. COLT Ilya O. Tolstikhin, Gilles Blanchard, Marius Kloft
2014	J	`jnl`	Localized Complexities for Transductive Learning. CoRR Ilya O. Tolstikhin, Gilles Blanchard, Marius Kloft
2014	J	`jnl`	Regularization-Based Multitask Learning With Applications to Genome Biology and Biological Imaging. Künstliche Intell. Christian Widmer, Marius Kloft, Xinghua Lou, Gunnar Rätsch
2014	J	`jnl`	Toward Supervised Anomaly Detection. CoRR Nico Görnitz, Marius Kloft, Konrad Rieck, Ulf Brefeld
2014	—	`conf`	When brain and behavior disagree: Tackling systematic label noise in EEG data with machine learning. BCI Anne K. Porbadnigk, Nico Görnitz, Claudia Sannelli, Alexander Binder, Mikio L. Braun, Marius Kloft, Klaus-Robert Müller
2013	J	`jnl`	Decoding Brain States during Auditory Perception by Supervising Unsupervised Learning. J. Comput. Sci. Eng. Anne Porbadnigk, Nico Görnitz, Marius Kloft, Klaus-Robert Müller
2013	J	`jnl`	Kernel-Based Machine Learning with Multiple Sources of Information. it Inf. Technol. Marius Kloft
2013	—	`conf`	Learning Kernels Using Local Rademacher Complexity. NIPS Corinna Cortes, Marius Kloft, Mehryar Mohri
2013	—	`conf`	Multi-task Learning for Computational Biology: Overview and Outlook. Empirical Inference Christian Widmer, Marius Kloft, Gunnar Rätsch
2013	J	`jnl`	Toward Supervised Anomaly Detection. J. Artif. Intell. Res. Nico Görnitz, Marius Kloft, Konrad Rieck, Ulf Brefeld
2012	—	`conf`	Early detection of malicious behavior in JavaScript code. AISec Kristof Schütt, Marius Kloft, Alexander Bikadorov, Konrad Rieck
2012	—	`conf`	Efficient Training of Graph-Regularized Multitask SVMs. ECML/PKDD (1) Christian Widmer, Marius Kloft, Nico Görnitz, Gunnar Rätsch
2012	J	`jnl`	On the convergence rate of lp-norm multiple kernel learning. J. Mach. Learn. Res. Marius Kloft, Gilles Blanchard
2012	J	`jnl`	Security analysis of online centroid anomaly detection. J. Mach. Learn. Res. Marius Kloft, Pavel Laskov
2011	—	`conf`	A new scatter-based multi-class support vector machine. MLSP Robert Jenssen, Marius Kloft, Sören Sonnenburg, Alexander Zien, Klaus-Robert Müller
2011	J	`jnl`	Insights from Classifying Visual Concepts with Multiple Kernel Learning CoRR Alexander Binder, Shinichi Nakajima, Marius Kloft, Christina Müller, Wojciech Samek, Ulf Brefeld, Klaus-Robert Müller, Motoaki Kawanabe
2011	—	`ch.`	Maschinelles Lernen mit multiplen Kernen. Ausgezeichnete Informatikdissertationen Marius Kloft
2011	—	`conf`	The Joint Submission of the TU Berlin and Fraunhofer FIRST (TUBFI) to the ImageCLEF2011 Photo Annotation Task. CLEF (Notebook Papers/Labs/Workshop) Alexander Binder, Wojciech Samek, Marius Kloft, Christina Müller, Klaus-Robert Müller, Motoaki Kawanabe
2011	—	`conf`	The Local Rademacher Complexity of Lp-Norm Multiple Kernel Learning. NIPS Marius Kloft, Gilles Blanchard
2011	—	`conf`	Transfer Learning with Adaptive Regularizers. ECML/PKDD (3) Ulrich Rückert, Marius Kloft
2011	—	`—`	lp-Norm Multiple Kernel Learning. Marius Kloft
2010	J	`jnl`	A Unifying View of Multiple Kernel Learning CoRR Marius Kloft, Ulrich Rückert, Peter L. Bartlett
2010	—	`conf`	A Unifying View of Multiple Kernel Learning. ECML/PKDD (2) Marius Kloft, Ulrich Rückert, Peter L. Bartlett
2010	J	`jnl`	Non-Sparse Regularization and Efficient Training with Multiple Kernels CoRR Marius Kloft, Ulf Brefeld, Sören Sonnenburg, Alexander Zien
2010	A	`conf`	Online Anomaly Detection under Adversarial Impact. AISTATS Marius Kloft, Pavel Laskov
2009	—	`conf`	A framework for quantitative security analysis of machine learning. AISec Pavel Laskov, Marius Kloft
2009	—	`conf`	Active and Semi-supervised Data Domain Description. ECML/PKDD (1) Nico Görnitz, Marius Kloft, Ulf Brefeld
2009	—	`conf`	Active learning for network intrusion detection. AISec Nico Görnitz, Marius Kloft, Konrad Rieck, Ulf Brefeld
2009	—	`conf`	Efficient and Accurate Lp-Norm Multiple Kernel Learning. NIPS Marius Kloft, Ulf Brefeld, Sören Sonnenburg, Pavel Laskov, Klaus-Robert Müller, Alexander Zien
2009	—	`conf`	Feature Selection for Density Level-Sets. ECML/PKDD (1) Marius Kloft, Shinichi Nakajima, Ulf Brefeld
2008	—	`conf`	Automatic feature selection for anomaly detection. AISec Marius Kloft, Ulf Brefeld, Patrick Düssel, Christian Gehl, Pavel Laskov