Marius Kloft

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

Achievements

+16 more ↓

🧭 Keyword Pioneer 🌍 Conference Polyglot (13) 🌉 Interdisciplinary Bridge 🗺️ Taxonomy Completionist (19) 🏃 Academic Marathon (16)

🌉 Interdisciplinary Bridge 🐣 Hot Topic Early Bird 🗺️ Taxonomy Completionist (19) 🤝 Dynamic Duo (11) 👑 Triple Crown 🌱 Topic Pioneer 🏆 Grand Slam 🔬 Deep Specialist (13) 🏆 Keyword Champion 🔥 Unstoppable (8) 📈 Trend Setter 🚀 Conference Pioneer ❓ The Questioner ⚡ Prolific Year (8) 💎 Century Club (44) 🗃️ 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 Pólya-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 Learning—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