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FedJAX: Federated learning simulation with JAX


Aug 04, 2021
Jae Hun Ro, Ananda Theertha Suresh, Ke Wu


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A Field Guide to Federated Optimization


Jul 14, 2021
Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Aguera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horvath, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecny, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtarik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu


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On the benefits of maximum likelihood estimation for Regression and Forecasting


Jun 18, 2021
Pranjal Awasthi, Abhimanyu Das, Rajat Sen, Ananda Theertha Suresh


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On the Renyi Differential Privacy of the Shuffle Model


May 11, 2021
Antonious M. Girgis, Deepesh Data, Suhas Diggavi, Ananda Theertha Suresh, Peter Kairouz


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Communication-Efficient Agnostic Federated Averaging


Apr 06, 2021
Jae Ro, Mingqing Chen, Rajiv Mathews, Mehryar Mohri, Ananda Theertha Suresh


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Remember What You Want to Forget: Algorithms for Machine Unlearning


Mar 04, 2021
Ayush Sekhari, Jayadev Acharya, Gautam Kamath, Ananda Theertha Suresh


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Learning with User-Level Privacy


Mar 02, 2021
Daniel Levy, Ziteng Sun, Kareem Amin, Satyen Kale, Alex Kulesza, Mehryar Mohri, Ananda Theertha Suresh

* 39 pages, 0 figure 

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Wyner-Ziv Estimators: Efficient Distributed Mean Estimation with Side Information


Nov 24, 2020
Prathamesh Mayekar, Ananda Theertha Suresh, Himanshu Tyagi


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Robust hypothesis testing and distribution estimation in Hellinger distance


Nov 03, 2020
Ananda Theertha Suresh


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Multiple-Source Adaptation with Domain Classifiers


Aug 25, 2020
Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh, Ningshan Zhang


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Shuffled Model of Federated Learning: Privacy, Communication and Accuracy Trade-offs


Aug 17, 2020
Antonious M. Girgis, Deepesh Data, Suhas Diggavi, Peter Kairouz, Ananda Theertha Suresh


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Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning


Aug 08, 2020
Sai Praneeth Karimireddy, Martin Jaggi, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Stich, Ananda Theertha Suresh


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Learning discrete distributions: user vs item-level privacy


Jul 28, 2020
Yuhan Liu, Ananda Theertha Suresh, Felix Yu, Sanjiv Kumar, Michael Riley

* 36 pages 

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Learning discrete distributions: user-lever vs item-level privacy


Jul 27, 2020
Yuhan Liu, Ananda Theertha Suresh, Felix Yu, Sanjiv Kumar, Michael Riley

* 36 pages 

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A Theory of Multiple-Source Adaptation with Limited Target Labeled Data


Jul 19, 2020
Yishay Mansour, Mehryar Mohri, Ananda Theertha Suresh, Ke Wu

* 20 pages 

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Relative Deviation Margin Bounds


Jun 26, 2020
Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh

* 29 pages 

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Three Approaches for Personalization with Applications to Federated Learning


Feb 25, 2020
Yishay Mansour, Mehryar Mohri, Jae Ro, Ananda Theertha Suresh

* 23 pages 

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Advances and Open Problems in Federated Learning


Dec 10, 2019
Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien 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, Adrià Gascón, 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 Konečný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao


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Can You Really Backdoor Federated Learning?


Dec 02, 2019
Ziteng Sun, Peter Kairouz, Ananda Theertha Suresh, H. Brendan McMahan

* To appear at the 2nd International Workshop on Federated Learning for Data Privacy and Confidentiality at NeurIPS 2019 

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SCAFFOLD: Stochastic Controlled Averaging for On-Device Federated Learning


Oct 14, 2019
Sai Praneeth Karimireddy, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Stich, Ananda Theertha Suresh


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Differentially private anonymized histograms


Oct 08, 2019
Ananda Theertha Suresh

* 24 pages 

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Federated Learning of N-gram Language Models


Oct 08, 2019
Mingqing Chen, Ananda Theertha Suresh, Rajiv Mathews, Adeline Wong, Cyril Allauzen, Françoise Beaufays, Michael Riley

* 10 pages 

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AdaCliP: Adaptive Clipping for Private SGD


Aug 20, 2019
Venkatadheeraj Pichapati, Ananda Theertha Suresh, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar

* 18 pages 

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Optimal multiclass overfitting by sequence reconstruction from Hamming queries


Aug 08, 2019
Jayadev Acharya, Ananda Theertha Suresh


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Sampled Softmax with Random Fourier Features


Jul 24, 2019
Ankit Singh Rawat, Jiecao Chen, Felix Yu, Ananda Theertha Suresh, Sanjiv Kumar


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Approximating probabilistic models as weighted finite automata


May 21, 2019
Ananda Theertha Suresh, Brian Roark, Michael Riley, Vlad Schogol


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Agnostic Federated Learning


Feb 01, 2019
Mehryar Mohri, Gary Sivek, Ananda Theertha Suresh

* 30 pages 

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WEST: Word Encoded Sequence Transducers


Nov 20, 2018
Ehsan Variani, Ananda Theertha Suresh, Mitchel Weintraub

* 12 pages 

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