Richard Nock

1. Advances and Open Problems in Federated Learning
   2019/12/10 by Peter Kairouz, H. Brendan McMahan, Kairouz, Peter +115 · 598 citations
   Computer Science · #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
2. Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach
   2016/09/13 by Giorgio Patrini, Alessandro Rozza, Patrini, Giorgio +7 · 43 citations
   Computer Science · #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
3. Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption
   2017/11/29 by Stephen Hardy, Hardy, Stephen, Wilko Henecka +11 · 63 citations
   Computer Science · #Privacy-Preserving Technologies in Data #Cryptography and Data Security #Stochastic Gradient Optimization Techniques
4. On the Centroids of Symmetrized Bregman Divergences
   2007/11/21 by Frank Nielsen, Richard Nock, Nielsen, Frank +1 · 3 citations
   Computer Science · Mathematics · Physics and Astronomy · #Advanced Statistical Methods and Models #Computational Geometry (cs.CG) #FOS: Computer and information sciences #Morphological variations and asymmetry #Statistical Mechanics and Entropy #cs.CG
5. Adversarial Networks and Autoencoders: The Primal-Dual Relationship and Generalization Bounds
   2019/02/03 by Hisham Husain, Husain, Hisham, Richard Nock +3 · 2 citations
   Computer Science · Physics and Astronomy · #Advanced Image Processing Techniques #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks
6. On w-mixtures: Finite convex combinations of prescribed component distributions
   2017/08/02 by Frank Nielsen, Nielsen, Frank, Richard Nock +1 · 1 citation
   Computer Science · Physics and Astronomy · #Bayesian Methods and Mixture Models #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Machine Learning (cs.LG) #Statistical Mechanics and Entropy
7. Clustering above Exponential Families with Tempered Exponential Measures
   2022/11/04 by Ehsan Amid, Richard Nock, Amid, Ehsan +3 · 1 citation
   Mathematics · Physics and Astronomy · Computer Science · #Advanced Statistical Methods and Models #Statistical Mechanics and Entropy #Bayesian Modeling and Causal Inference
8. Manifold Learning Benefits GANs
   2021/12/23 by Yao Ni, Ni, Yao, Piotr Koniusz +5 · 1 citation
   Computer Science · #Advanced Vision and Imaging #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Human Pose and Action Recognition #Machine Learning (cs.LG)
9. All your loss are belong to Bayes
   2020/06/08 by Christian Walder, Walder, Christian, Richard Nock +1 · 1 citation
   Computer Science · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification
10. Being Properly Improper
    2021/06/18 by Tyler Sypherd, Sypherd, Tyler, Richard Nock +3 · 1 citation
    Computer Science · #Adversarial Robustness in Machine Learning #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Mathematics #I.2.6 #Machine Learning (cs.LG) #Machine Learning and Algorithms #Machine Learning and Data Classification #Optimization and Control (math.OC)