Anastasia Koloskova | DeepAI

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∙ 05/30/2023

Shuffle SGD is Always Better than SGD: Improved Analysis of SGD with Arbitrary Data Orders

Stochastic Gradient Descent (SGD) algorithms are widely used in optimizi...

0 Anastasia Koloskova, et al. ∙

∙ 05/02/2023

Revisiting Gradient Clipping: Stochastic bias and tight convergence guarantees

Gradient clipping is a popular modification to standard (stochastic) gra...

0 Anastasia Koloskova, et al. ∙

∙ 02/02/2023

Convergence of Gradient Descent with Linearly Correlated Noise and Applications to Differentially Private Learning

We study stochastic optimization with linearly correlated noise. Our stu...

0 Anastasia Koloskova, et al. ∙

∙ 01/03/2023

Decentralized Gradient Tracking with Local Steps

Gradient tracking (GT) is an algorithm designed for solving decentralize...

0 Yue Liu, et al. ∙

∙ 06/16/2022

Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning

We study the asynchronous stochastic gradient descent algorithm for dist...

0 Anastasia Koloskova, et al. ∙

∙ 04/13/2022

Data-heterogeneity-aware Mixing for Decentralized Learning

Decentralized learning provides an effective framework to train machine ...

11 Yatin Dandi, et al. ∙

∙ 02/08/2022

An Improved Analysis of Gradient Tracking for Decentralized Machine Learning

We consider decentralized machine learning over a network where the trai...

0 Anastasia Koloskova, et al. ∙

∙ 10/08/2021

RelaySum for Decentralized Deep Learning on Heterogeneous Data

In decentralized machine learning, workers compute model updates on thei...

0 Thijs Vogels, et al. ∙

∙ 06/15/2021

Decentralized Local Stochastic Extra-Gradient for Variational Inequalities

We consider decentralized stochastic variational inequalities where the ...

0 Aleksandr Beznosikov, et al. ∙

∙ 02/09/2021

Consensus Control for Decentralized Deep Learning

Decentralized training of deep learning models enables on-device learnin...

0 Lingjing Kong, et al. ∙

∙ 11/03/2020

A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free!

Decentralized optimization methods enable on-device training of machine ...

22 Dmitry Kovalev, et al. ∙

∙ 03/23/2020

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

Decentralized stochastic optimization methods have gained a lot of atten...

0 Anastasia Koloskova, et al. ∙

∙ 07/22/2019

Decentralized Deep Learning with Arbitrary Communication Compression

Decentralized training of deep learning models is a key element for enab...

0 Anastasia Koloskova, et al. ∙

∙ 02/01/2019

Decentralized Stochastic Optimization and Gossip Algorithms with Compressed Communication

We consider decentralized stochastic optimization with the objective fun...

0 Anastasia Koloskova, et al. ∙

∙ 10/16/2018

Efficient Greedy Coordinate Descent for Composite Problems

Coordinate descent with random coordinate selection is the current state...

0 Sai Praneeth Karimireddy, et al. ∙

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