Richard Nock
Richard Nock
Google Research
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Cited by
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Advances and open problems in federated learning
P Kairouz, HB McMahan, B Avent, A Bellet, M Bennis, AN Bhagoji, ...
Foundations and Trends® in Machine Learning 14 (1–2), 1-210, 2021
Statistical region merging
R Nock, F Nielsen
IEEE Transactions on pattern analysis and machine intelligence 26 (11), 1452 …, 2004
Making deep neural networks robust to label noise: A loss correction approach
G Patrini, A Rozza, A Krishna Menon, R Nock, L Qu
Proceedings of the IEEE conference on computer vision and pattern …, 2017
Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption
S Hardy, W Henecka, H Ivey-Law, R Nock, G Patrini, G Smith, B Thorne
arXiv preprint arXiv:1711.10677, 2017
On weighting clustering
R Nock, F Nielsen
IEEE transactions on pattern analysis and machine intelligence 28 (8), 1223-1235, 2006
Adaptive subspaces for few-shot learning
C Simon, P Koniusz, R Nock, M Harandi
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
Sided and symmetrized Bregman centroids
F Nielsen, R Nock
IEEE transactions on Information Theory 55 (6), 2882-2904, 2009
A hybrid filter/wrapper approach of feature selection using information theory
M Sebban, R Nock
Pattern recognition 35 (4), 835-846, 2002
On the chi square and higher-order chi distances for approximating f-divergences
F Nielsen, R Nock
IEEE Signal Processing Letters 21 (1), 10-13, 2013
Bregman voronoi diagrams
JD Boissonnat, F Nielsen, R Nock
Discrete & Computational Geometry 44 (2), 281-307, 2010
Bregman Voronoi diagrams: Properties, algorithms and applications
F Nielsen, JD Boissonnat, R Nock
arXiv preprint arXiv:0709.2196, 2007
Learning and evaluation in the presence of class hierarchies: Application to text categorization
S Kiritchenko, S Matwin, R Nock, AF Famili
Conference of the Canadian Society for Computational Studies of Intelligence …, 2006
Loss factorization, weakly supervised learning and label noise robustness
G Patrini, F Nielsen, R Nock, M Carioni
International conference on machine learning, 708-717, 2016
Entropies and cross-entropies of exponential families
F Nielsen, R Nock
2010 IEEE International Conference on Image Processing, 3621-3624, 2010
Bregman divergences and surrogates for learning
R Nock, F Nielsen
IEEE Transactions on Pattern Analysis and Machine Intelligence 31 (11), 2048 …, 2008
A closed-form expression for the Sharma–Mittal entropy of exponential families
F Nielsen, R Nock
Journal of Physics A: Mathematical and Theoretical 45 (3), 032003, 2011
Entity resolution and federated learning get a federated resolution
R Nock, S Hardy, W Henecka, H Ivey-Law, G Patrini, G Smith, B Thorne
arXiv preprint arXiv:1803.04035, 2018
Fitting the smallest enclosing Bregman ball
R Nock, F Nielsen
European Conference on Machine Learning, 649-656, 2005
Semi-supervised statistical region refinement for color image segmentation
R Nock, F Nielsen
Pattern Recognition 38 (6), 835-846, 2005
Approximating smallest enclosing balls with applications to machine learning
F Nielsen, R Nock
International Journal of Computational Geometry & Applications 19 (05), 389-414, 2009
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