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All your loss are belong to Bayes

Jun 08, 2020
Christian Walder, Richard Nock


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Cumulant-free closed-form formulas for some common (dis)similarities between densities of an exponential family

Apr 07, 2020
Frank Nielsen, Richard Nock

* 33 pages 

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Generalised Lipschitz Regularisation Equals Distributional Robustness

Feb 11, 2020
Zac Cranko, Zhan Shi, Xinhua Zhang, Richard Nock, Simon Kornblith


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Supervised Learning: No Loss No Cry

Feb 10, 2020
Richard Nock, Aditya Krishna Menon


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Boosted and Differentially Private Ensembles of Decision Trees

Feb 03, 2020
Richard Nock, Wilko Henecka


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Advances and Open Problems in Federated Learning

Dec 10, 2019
Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aur√©lien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Keith Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adri√† Gasc√≥n, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaid Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Koneńćn√Ĺ, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancr√®de Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer √Ėzg√ľr, Rasmus Pagh, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tram√®r, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao


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Proper-Composite Loss Functions in Arbitrary Dimensions

Feb 19, 2019
Zac Cranko, Robert C. Williamson, Richard Nock


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Adversarial Networks and Autoencoders: The Primal-Dual Relationship and Generalization Bounds

Feb 03, 2019
Hisham Husain, Richard Nock, Robert C. Williamson


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New Tricks for Estimating Gradients of Expectations

Jan 31, 2019
Christian J. Walder, Richard Nock, Cheng Soon Ong, Masashi Sugiyama


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The Bregman chord divergence

Oct 22, 2018
Frank Nielsen, Richard Nock

* 10 pages 

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Hyperparameter Learning for Conditional Mean Embeddings with Rademacher Complexity Bounds

Sep 19, 2018
Kelvin Hsu, Richard Nock, Fabio Ramos

* Best Student Machine Learning Paper Award Winner at ECML-PKDD 2018 (European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases) 

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Monge beats Bayes: Hardness Results for Adversarial Training

Sep 12, 2018
Zac Cranko, Aditya Krishna Menon, Richard Nock, Cheng-Soon Ong, Zhan Shi, Christian Walder


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Integral Privacy for Sampling from Mollifier Densities with Approximation Guarantees

Sep 12, 2018
Hisham Husain, Zac Cranko, Richard Nock


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Lipschitz Networks and Distributional Robustness

Sep 04, 2018
Zac Cranko, Simon Kornblith, Zhan Shi, Richard Nock


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D-PAGE: Diverse Paraphrase Generation

Aug 13, 2018
Qiongkai Xu, Juyan Zhang, Lizhen Qu, Lexing Xie, Richard Nock


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Private Text Classification

Jun 19, 2018
Leif W. Hanlen, Richard Nock, Hanna Suominen, Neil Bacon

* 10 pages, 3 figures 

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Boosted Density Estimation Remastered

Jun 18, 2018
Zac Cranko, Richard Nock

* Contains lots of essential info 

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Entity Resolution and Federated Learning get a Federated Resolution

Mar 20, 2018
Richard Nock, Stephen Hardy, Wilko Henecka, Hamish Ivey-Law, Giorgio Patrini, Guillaume Smith, Brian Thorne

* arXiv admin note: text overlap with arXiv:1711.10677 

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Evolving a Vector Space with any Generating Set

Dec 31, 2017
Richard Nock, Frank Nielsen


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Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption

Nov 29, 2017
Stephen Hardy, Wilko Henecka, Hamish Ivey-Law, Richard Nock, Giorgio Patrini, Guillaume Smith, Brian Thorne


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On $w$-mixtures: Finite convex combinations of prescribed component distributions

Aug 02, 2017
Frank Nielsen, Richard Nock

* 25 pages 

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f-GANs in an Information Geometric Nutshell

Jul 14, 2017
Richard Nock, Zac Cranko, Aditya Krishna Menon, Lizhen Qu, Robert C. Williamson


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Generalizing Jensen and Bregman divergences with comparative convexity and the statistical Bhattacharyya distances with comparable means

May 03, 2017
Frank Nielsen, Richard Nock

* 24 pages 

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Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach

Mar 22, 2017
Giorgio Patrini, Alessandro Rozza, Aditya Menon, Richard Nock, Lizhen Qu

* Oral paper at CVPR 2017 

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The Crossover Process: Learnability and Data Protection from Inference Attacks

Mar 07, 2017
Richard Nock, Giorgio Patrini, Finnian Lattimore, Tiberio Caetano


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Semi-parametric Network Structure Discovery Models

Feb 27, 2017
Amir Dezfouli, Edwin V. Bonilla, Richard Nock


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A series of maximum entropy upper bounds of the differential entropy

Dec 09, 2016
Frank Nielsen, Richard Nock

* 18 pages 

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Large Margin Nearest Neighbor Classification using Curved Mahalanobis Distances

Sep 26, 2016
Frank Nielsen, Boris Muzellec, Richard Nock

* 21 pages, 8 figures, 5 tables, extend ICIP 2016 paper entitled "classification With Mixtures of Curved Mahalanobis Metrics" 

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