← Authors

Marius Kloft

47 papers · 2009–2026 · 14 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer πŸƒ Academic Marathon (16) 🌍 Conference Polyglot (13) 🐝 Cross-Pollinator (15) 🌈 Renaissance Researcher (8) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (19) 🀝 Dynamic Duo (11) πŸ‘‘ Triple Crown 🌱 Topic Pioneer πŸ† Grand Slam πŸ”¬ Deep Specialist (13) πŸ† Keyword Champion πŸ”₯ Unstoppable (8) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer ❓ The Questioner ⚑ Prolific Year (8) πŸ’Ž Century Club (44) πŸ—ƒοΈ Keyword Collector (59)

Conferences

NIPS (9) AAAI (7) ICML (7) AISTATS (5) IJCAI (4) JMLR (4) ACL (3) ICLR (2) ACML (1) COLING (1) COLT (1) EACL (1) EMNLP (1) NAACL (1)

Top co-authors

Yunwen Lei (11) Antoine Ledent (10) Sophie Fellenz (8) Waleed Mustafa (7) Stephan Mandt (6) Chen Qiu (5) Alexander Binder (5) Maja Rudolph (5) Philipp Liznerski (4) Lukas Ruff (4)

Research topics

Computer Vision (1)

Keywords

generalization bound (9) anomaly detection (7) kernel methods (6) multiple kernel learning (5) representation learning (5) rademacher complexity (4) multi-class classification (4) online learning (4) excess risk bound (3) local rademacher complexity (3) adversarial learning (3) variational inference (3) learning theory (3) self-supervised learning (3) support vector machine (3) one-class classification (3) neural network (3) lp-norm optimization (2) gaussian process (2) text style transfer (2)

Papers

Reimagining Anomalies: What If Anomalies Were Normal? AAAI 2026
TORA: Train Once, Realign Anytime for Offline Multi-Objective Reinforcement Learning AAAI 2026
Continual Neural Topic Model EACL 2026
Challenging Assumptions in Learning Generic Text Style Embeddings NAACL 2025
Characterizing Text Datasets with Psycholinguistic Features EMNLP 2024
Interpretable Tensor Fusion IJCAI 2024
Evaluating Dynamic Topic Models ACL 2024
Non-vacuous Generalization Bounds for Adversarial Risk in Stochastic Neural Networks AISTATS 2024
Text Style Transfer Evaluation Using Large Language Models COLING 2024
A Call for Standardization and Validation of Text Style Transfer Evaluation ACL 2023
Zero-Shot Anomaly Detection via Batch Normalization NIPS 2023
Labeling Neural Representations with Inverse Recognition NIPS 2023
Training Normalizing Flows from Dependent Data ICML 2023
Generalization Bounds for Inductive Matrix Completion in Low-Noise Settings AAAI 2023
Deep Anomaly Detection under Labeling Budget Constraints ICML 2023
Raising the Bar in Graph-level Anomaly Detection IJCAI 2022
Latent Outlier Exposure for Anomaly Detection with Contaminated Data ICML 2022
On the Generalization Analysis of Adversarial Learning ICML 2022
Fine-grained Generalization Analysis of Structured Output Prediction IJCAI 2021
Fine-grained Generalization Analysis of Vector-Valued Learning AAAI 2021
Norm-Based Generalisation Bounds for Deep Multi-Class Convolutional Neural Networks AAAI 2021
Neural Transformation Learning for Deep Anomaly Detection Beyond Images ICML 2021
Model Uncertainty Guides Visual Object Tracking AAAI 2021
Fine-grained Generalization Analysis of Inductive Matrix Completion NIPS 2021
Explainable Deep One-Class Classification ICLR 2021
Learning Interpretable Concept Groups in CNNs IJCAI 2021
Sharper Generalization Bounds for Pairwise Learning NIPS 2020
Two-sample Testing Using Deep Learning AISTATS 2020
Deep Semi-Supervised Anomaly Detection ICLR 2020
Effective End-to-end Unsupervised Outlier Detection via Inlier Priority of Discriminative Network NIPS 2019
Self-Attentive, Multi-Context One-Class Classification for Unsupervised Anomaly Detection on Text ACL 2019
Efficient Gaussian Process Classification Using PΓ³lya-Gamma Data Augmentation AAAI 2019
Scalable Generalized Dynamic Topic Models AISTATS 2018
Deep One-Class Classification ICML 2018
Local Rademacher Complexity-based Learning Guarantees for Multi-Task Learning JMLR 2018
Localized Multiple Kernel Learningβ€”A Convex Approach ACML 2016
Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms NIPS 2015
Hidden Markov Anomaly Detection ICML 2015
Learning and Evaluation in Presence of Non-i.i.d. Label Noise AISTATS 2014
Localized Complexities for Transductive Learning COLT 2014
Learning Kernels Using Local Rademacher Complexity NIPS 2013
Security Analysis of Online Centroid Anomaly Detection JMLR 2012
On the Convergence Rate of -Norm Multiple Kernel Learning JMLR 2012
The Local Rademacher Complexity of Lp-Norm Multiple Kernel Learning NIPS 2011
-Norm Multiple Kernel Learning JMLR 2011
Online Anomaly Detection under Adversarial Impact AISTATS 2010
Efficient and Accurate Lp-Norm Multiple Kernel Learning NIPS 2009