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On Communication Compression for Distributed Optimization on Heterogeneous Data

Sep 04, 2020
Sebastian U. Stich


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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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Analysis of SGD with Biased Gradient Estimators

Jul 31, 2020
Ahmad Ajalloeian, Sebastian U. Stich

* Accepted to ICML 2020 Workshop "Beyond First Order Methods in ML Systems" 

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Dynamic Model Pruning with Feedback

Jun 12, 2020
Tao Lin, Sebastian U. Stich, Luis Barba, Daniil Dmitriev, Martin Jaggi

* appearing at ICLR 2020 

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Ensemble Distillation for Robust Model Fusion in Federated Learning

Jun 12, 2020
Tao Lin, Lingjing Kong, Sebastian U. Stich, Martin Jaggi


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Extrapolation for Large-batch Training in Deep Learning

Jun 10, 2020
Tao Lin, Lingjing Kong, Sebastian U. Stich, Martin Jaggi


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A Unified Theory of Decentralized SGD with Changing Topology and Local Updates

Mar 23, 2020
Anastasia Koloskova, Nicolas Loizou, Sadra Boreiri, Martin Jaggi, Sebastian U. Stich


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Is Local SGD Better than Minibatch SGD?

Feb 18, 2020
Blake Woodworth, Kumar Kshitij Patel, Sebastian U. Stich, Zhen Dai, Brian Bullins, H. Brendan McMahan, Ohad Shamir, Nathan Srebro

* 29 pages 

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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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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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The Error-Feedback Framework: Better Rates for SGD with Delayed Gradients and Compressed Communication

Sep 11, 2019
Sebastian U. Stich, Sai Praneeth Karimireddy


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Decentralized Deep Learning with Arbitrary Communication Compression

Jul 22, 2019
Anastasia Koloskova, Tao Lin, Sebastian U. Stich, Martin Jaggi


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Unified Optimal Analysis of the (Stochastic) Gradient Method

Jul 09, 2019
Sebastian U. Stich

* 9 pages 

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Decentralized Stochastic Optimization and Gossip Algorithms with Compressed Communication

Feb 01, 2019
Anastasia Koloskova, Sebastian U. Stich, Martin Jaggi


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Error Feedback Fixes SignSGD and other Gradient Compression Schemes

Jan 28, 2019
Sai Praneeth Karimireddy, Quentin Rebjock, Sebastian U. Stich, Martin Jaggi


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Don't Use Large Mini-Batches, Use Local SGD

Oct 21, 2018
Tao Lin, Sebastian U. Stich, Martin Jaggi


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Efficient Greedy Coordinate Descent for Composite Problems

Oct 16, 2018
Sai Praneeth Karimireddy, Anastasia Koloskova, Sebastian U. Stich, Martin Jaggi

* 44 pages, 17 figures, 3 tables 

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k-SVRG: Variance Reduction for Large Scale Optimization

Oct 16, 2018
Anant Raj, Sebastian U. Stich

* The title of the previous version of the manuscript was "SVRG meets SAGA: k-SVRG A Tale of Limited Memory" 

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Sparsified SGD with Memory

Sep 20, 2018
Sebastian U. Stich, Jean-Baptiste Cordonnier, Martin Jaggi

* to appear at NIPS 2018 

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On Matching Pursuit and Coordinate Descent

Jul 02, 2018
Francesco Locatello, Anant Raj, Sai Praneeth Karimireddy, Gunnar Rätsch, Bernhard Schölkopf, Sebastian U. Stich, Martin Jaggi

* ICML 2018 - Proceedings of the 35th International Conference on Machine Learning 

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Local SGD Converges Fast and Communicates Little

Jun 25, 2018
Sebastian U. Stich

* preprint, 12 pages 

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Global linear convergence of Newton's method without strong-convexity or Lipschitz gradients

Jun 01, 2018
Sai Praneeth Karimireddy, Sebastian U. Stich, Martin Jaggi

* 19 pages 

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Safe Adaptive Importance Sampling

Nov 07, 2017
Sebastian U. Stich, Anant Raj, Martin Jaggi

* To appear at NIPS 2017 

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Approximate Steepest Coordinate Descent

Jun 26, 2017
Sebastian U. Stich, Anant Raj, Martin Jaggi

* appearing at ICML 2017 

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