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Sai Praneeth Karimireddy
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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PowerGossip: Practical Low-Rank Communication Compression in Decentralized Deep Learning

Aug 04, 2020
Thijs Vogels, Sai Praneeth Karimireddy, Martin Jaggi


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Byzantine-Robust Learning on Heterogeneous Datasets via Resampling

Jun 23, 2020
Lie He, Sai Praneeth Karimireddy, Martin Jaggi


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Secure Byzantine-Robust Machine Learning

Jun 08, 2020
Lie He, Sai Praneeth Karimireddy, Martin Jaggi


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Why ADAM Beats SGD for Attention Models

Dec 06, 2019
Jingzhao Zhang, Sai Praneeth Karimireddy, Andreas Veit, Seungyeon Kim, Sashank J Reddi, Sanjiv Kumar, Suvrit Sra


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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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Amplifying Rényi Differential Privacy via Shuffling

Jul 26, 2019
Eloïse Berthier, Sai Praneeth Karimireddy

* This version (and v1) have incorrect proofs! We are currently working on fixing these 

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PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization

May 31, 2019
Thijs Vogels, Sai Praneeth Karimireddy, Martin Jaggi


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Accelerating Gradient Boosting Machine

Mar 20, 2019
Haihao Lu, Sai Praneeth Karimireddy, Natalia Ponomareva, Vahab Mirrokni


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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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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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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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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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