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Kloft, Marius

  1. Deep Semi-Supervised Anomaly Detection
    2019/06/06 by Ruff, Lukas, Vandermeulen, Robert A., Görnitz, Nico +4 · 25 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  2. Explainable Deep One-Class Classification
    2020/07/03 by Liznerski, Philipp, Ruff, Lukas, Vandermeulen, Robert A. +3 · 16 citations
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  3. Security Analysis of Online Centroid Anomaly Detection
    2010/02/27 by Marius Kloft, Pavel Laskov, Kloft, Marius +1 · 8 citations
    Computer Science · #Network Security and Intrusion Detection #Anomaly Detection Techniques and Applications #Spam and Phishing Detection
  4. On the Challenges and Opportunities in Generative AI
    2024/02/28 by Laura Manduchi, Manduchi, Laura, Kushagra Pandey +48 · 9 citations
    Computer Science · #AI-based Problem Solving and Planning #Cognitive Computing and Networks #Evolutionary Algorithms and Applications
  5. Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to\n Novel Algorithms
    2015/06/14 by Yunwen Lei, Lei, Yunwen, Ürün Doǧan +5 · 4 citations
    Computer Science · #FOS: Computer and information sciences #Face and Expression Recognition #Machine Learning (cs.LG) #Machine Learning and Algorithms #Machine Learning and ELM
  6. Rethinking Assumptions in Deep Anomaly Detection
    2020/05/30 by Ruff, Lukas, Vandermeulen, Robert A., Franks, Billy Joe +2 · 3 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  7. Local Rademacher Complexity-based Learning Guarantees for Multi-Task Learning
    2016/02/18 by Niloofar Yousefi, Yousefi, Niloofar, Yunwen Lei +7 · 2 citations
    Computer Science · Engineering · #Machine Learning and Algorithms #Stochastic Gradient Optimization Techniques #Sparse and Compressive Sensing Techniques
  8. Efficient Gaussian Process Classification Using Polya-Gamma Data Augmentation
    2018/02/18 by Wenzel, Florian, Galy-Fajou, Theo, Donner, Christan +2 · 2 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  9. How Much Can I Trust You? -- Quantifying Uncertainties in Explaining Neural Networks
    2020/06/16 by Kirill Bykov, Marina Höhne, Bykov, Kirill +7 · 2 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  10. Deep Anomaly Detection on Tennessee Eastman Process Data
    2023/03/10 by Hartung, Fabian, Franks, Billy Joe, Michels, Tobias +15 · 3 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
  11. Explaining Bayesian Neural Networks
    2021/08/23 by Bykov, Kirill, Höhne, Marina M. -C., Creosteanu, Adelaida +4 · 2 citations
    #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  12. Detecting Anomalies within Time Series using Local Neural Transformations
    2022/02/08 by Schneider, Tim, Qiu, Chen, Kloft, Marius +4 · 2 citations
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  13. Evaluating Dynamic Topic Models
    2023/09/12 by Charu Karakkaparambil James, Mayank Nagda, James, Charu +7 · 2 citations
    Computer Science · Social Sciences · #Advanced Text Analysis Techniques #Computation and Language (cs.CL) #Computational and Text Analysis Methods #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Machine Learning (cs.LG) #Topic Modeling
  14. Localized Multiple Kernel Learning---A Convex Approach
    2015/06/14 by Yunwen Lei, Lei, Yunwen, Alexander Binder +5 · 1 citation
    Computer Science · Engineering · #Face and Expression Recognition #Sparse and Compressive Sensing Techniques #Neural Networks and Applications
  15. AI-based Anomaly Detection for Clinical-Grade Histopathological Diagnostics
    2024/06/21 by Jonas Dippel, Niklas Prenißl, Dippel, Jonas +23 · 2 citations
    Medicine · Computer Science · #COVID-19 diagnosis using AI #Artificial Intelligence in Healthcare and Education #AI in cancer detection
  16. Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images
    2022/05/23 by Philipp Liznerski, Liznerski, Philipp, Lukas Ruff +9 · 2 citations
    Computer Science · Medicine · #Anomaly Detection Techniques and Applications #COVID-19 diagnosis using AI #Computer Vision and Pattern Recognition (cs.CV) #Data-Driven Disease Surveillance #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  17. Feature Importance Measure for Non-linear Learning Algorithms
    2016/11/22 by Marina M.-C. Vidovic, Vidovic, Marina M. -C., Nico Görnitz +5 · 1 citation
    Computer Science · #Anomaly Detection Techniques and Applications #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Neural Networks and Applications
  18. Zero-Shot Anomaly Detection via Batch Normalization
    2023/02/15 by Aodong Li, Chen Qiu, Li, Aodong +9 · 1 citation
    Computer Science · Medicine · #Anomaly Detection Techniques and Applications #COVID-19 diagnosis using AI #Domain Adaptation and Few-Shot Learning
  19. Fine-grained Generalization Analysis of Vector-valued Learning
    2021/04/29 by Wu, Liang, Ledent, Antoine, Lei, Yunwen +1 · 1 citation
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  20. Fine-grained Generalization Analysis of Structured Output Prediction
    2021/05/31 by Mustafa, Waleed, Lei, Yunwen, Ledent, Antoine +1 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  21. Interpretable Tensor Fusion
    2024/05/07 by Saurabh Varshneya, Antoine Ledent, Varshneya, Saurabh +11 · 1 citation
    Computer Science · Physics and Astronomy · #Computational Physics and Python Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Model Reduction and Neural Networks
  22. Anomaly Detection of Tabular Data Using LLMs
    2024/06/24 by Aodong Li, Li, Aodong, Yunhan Zhao +11 · 1 citation
    Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #Computational Physics and Python Applications #FOS: Computer and information sciences #Machine Learning (cs.LG)
  23. SetPINNs: Set-based Physics-informed Neural Networks
    2024/09/30 by Mayank Nagda, Nagda, Mayank, Phil Ostheimer +12 · 1 citation
    Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Neural Networks and Applications