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Adaptive Stochastic Gradient Descent for Fast and Communication-Efficient Distributed Learning


Aug 04, 2022
Serge Kas Hanna, Rawad Bitar, Parimal Parag, Venkat Dasari, Salim El Rouayheb

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* arXiv admin note: substantial text overlap with arXiv:2002.11005 

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Walk for Learning: A Random Walk Approach for Federated Learning from Heterogeneous Data


Jun 01, 2022
Ghadir Ayache, Venkat Dassari, Salim El Rouayheb

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Private Weighted Random Walk Stochastic Gradient Descent


Sep 03, 2020
Ghadir Ayache, Salim El Rouayheb

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Mechanisms for Hiding Sensitive Genotypes with Information-Theoretic Privacy


Jul 10, 2020
Fangwei Ye, Hyunghoon Cho, Salim El Rouayheb

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* A full version of a paper accepted by ISIT 2020. A video talk of this paper can be found at https://www.youtube.com/watch?v=VxqGDbJ8uN8 

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Adaptive Distributed Stochastic Gradient Descent for Minimizing Delay in the Presence of Stragglers


Feb 25, 2020
Serge Kas Hanna, Rawad Bitar, Parimal Parag, Venkat Dasari, Salim El Rouayheb

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* Accepted to IEEE ICASSP 2020 

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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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