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Moeller, Michael

  1. Inverting Gradients -- How easy is it to break privacy in federated learning?
    2020/03/31 by Jonas Geiping, Geiping, Jonas, Hartmut Bauermeister +5 · 104 citations
    Computer Science · #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning #Computer Vision and Pattern Recognition (cs.CV) #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Privacy-Preserving Technologies in Data
  2. Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching
    2020/09/04 by Jonas Geiping, Geiping, Jonas, Liam Fowl +11 · 13 citations
    Computer Science · #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  3. WEAR: An Outdoor Sports Dataset for Wearable and Egocentric Activity Recognition
    2023/04/11 by Marius Bock, Bock, Marius, Hilde Kuehne +5 · 11 citations
    Computer Science · Engineering · #Human Pose and Action Recognition #Context-Aware Activity Recognition Systems #Gait Recognition and Analysis
  4. Stochastic Training is Not Necessary for Generalization
    2021/09/29 by Jonas Geiping, Geiping, Jonas, Micah Goldblum +7 · 6 citations
    Computer Science · #Advanced Neural Network Applications #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Optimization and Control (math.OC) #Stochastic Gradient Optimization Techniques
  5. What Doesn't Kill You Makes You Robust(er): How to Adversarially Train against Data Poisoning
    2021/02/26 by Jonas Geiping, Geiping, Jonas, Liam Fowl +9 · 3 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Computer Vision and Pattern Recognition (cs.CV) #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  6. Intrinsic Neural Fields: Learning Functions on Manifolds
    2022/03/15 by Lukas Koestler, Daniel Grittner, Koestler, Lukas +7 · 2 citations
    Computer Science · #Generative Adversarial Networks and Image Synthesis #Advanced Neural Network Applications #Human Pose and Action Recognition
  7. Truth or Backpropaganda? An Empirical Investigation of Deep Learning Theory
    2019/10/01 by Micah Goldblum, Jonas Geiping, Goldblum, Micah +7 · 2 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #FOS: Mathematics #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  8. The Primal-Dual Hybrid Gradient Method for Semiconvex Splittings
    2014/07/07 by Möllenhoff, Thomas, Strekalovskiy, Evgeny, Moeller, Michael +1 · 1 citation
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Mathematics #Numerical Analysis (math.NA) #Optimization and Control (math.OC)
  9. Nonlinear Spectral Analysis via One-homogeneous Functionals - Overview and Future Prospects
    2015/10/05 by Gilboa, Guy, Moeller, Michael, Burger, Martin · 1 citation
    #35A15 #35A22 #35P30 #68U10 #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Mathematics #Numerical Analysis (math.NA) #Spectral Theory (math.SP)
  10. DS*: Tighter Lifting-Free Convex Relaxations for Quadratic Matching Problems
    2017/11/29 by Florian Bernard, Bernard, Florian, Christian Theobalt +3 · 1 citation
    Computer Science · #Advanced Graph Theory Research #Complexity and Algorithms in Graphs #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Optimization and Search Problems
  11. Spectral Decompositions using One-Homogeneous Functionals
    2016/01/12 by Burger, Martin, Gilboa, Guy, Moeller, Michael +2 · 1 citation
    #FOS: Mathematics #Numerical Analysis (math.NA) #Optimization and Control (math.OC) #Spectral Theory (math.SP)
  12. Training or Architecture? How to Incorporate Invariance in Neural Networks
    2021/06/18 by Kanchana Vaishnavi Gandikota, Jonas Geiping, Gandikota, Kanchana Vaishnavi +6 · 1 citation
    Computer Science · #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Image Processing and 3D Reconstruction
  13. An Evaluation of Zero-Cost Proxies -- from Neural Architecture Performance to Model Robustness
    2023/07/18 by Jovita Lukasik, Michael Moeller, Lukasik, Jovita +3 · 2 citations
    Computer Science · Materials Science · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning in Materials Science
  14. Proximal Backpropagation
    2017/06/14 by Thomas Frerix, Thomas Möllenhoff, Frerix, Thomas +5 · 1 citation
    Computer Science · #Advanced Neural Network Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and ELM #Stochastic Gradient Optimization Techniques
  15. SIGMA: Scale-Invariant Global Sparse Shape Matching
    2023/08/16 by Maolin Gao, Paul Roetzer, Gao, Maolin +11 · 1 citation
    Engineering · Computer Science · #3D Shape Modeling and Analysis #Robotics and Sensor-Based Localization #Human Pose and Action Recognition
  16. Training Data Reconstruction: Privacy due to Uncertainty?
    2024/12/11 by Christina Runkel, Runkel, Christina, Kanchana Vaishnavi Gandikota +7 · 2 citations
    Computer Science · #Privacy-Preserving Technologies in Data
  17. Convergent Data-driven Regularizations for CT Reconstruction
    2022/12/14 by Kabri, Samira, Auras, Alexander, Riccio, Danilo +4 · 1 citation
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #Image and Video Processing (eess.IV) #Machine Learning (cs.LG) #Numerical Analysis (math.NA) #electronic engineering #information engineering
  18. CCuantuMM: Cycle-Consistent Quantum-Hybrid Matching of Multiple Shapes
    2023/03/28 by Harshil Bhatia, Edith Tretschk, Bhatia, Harshil +11 · 1 citation
    Computer Science · #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Graph Theory and Algorithms #Parallel Computing and Optimization Techniques
  19. QuAnt: Quantum Annealing with Learnt Couplings
    2022/10/13 by Marcel Seelbach Benkner, Maximilian Krahn, Benkner, Marcel Seelbach +9 · 1 citation
    Computer Science · #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Physical sciences #Graph Theory and Algorithms #Machine Learning (cs.LG) #Quantum Computing Algorithms and Architecture #Quantum Physics (quant-ph)
  20. Differentiable Sensor Layouts for End-to-End Learning of Task-Specific Camera Parameters
    2023/04/28 by Sommerhoff, Hendrik, Agnihotri, Shashank, Saleh, Mohamed +3 · 1 citation
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences