Anastasia Koloskova

Affiliations:
  • EPFL, Lausanne, Switzerland


According to our database1, Anastasia Koloskova authored at least 17 papers between 2019 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
Asynchronous SGD on Graphs: a Unified Framework for Asynchronous Decentralized and Federated Optimization.
CoRR, 2023

Shuffle SGD is Always Better than SGD: Improved Analysis of SGD with Arbitrary Data Orders.
CoRR, 2023

Convergence of Gradient Descent with Linearly Correlated Noise and Applications to Differentially Private Learning.
CoRR, 2023

Decentralized Gradient Tracking with Local Steps.
CoRR, 2023

Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential Privacy.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Revisiting Gradient Clipping: Stochastic bias and tight convergence guarantees.
Proceedings of the International Conference on Machine Learning, 2023

2022
Data-heterogeneity-aware Mixing for Decentralized Learning.
CoRR, 2022

Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Decentralized Local Stochastic Extra-Gradient for Variational Inequalities.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
RelaySum for Decentralized Deep Learning on Heterogeneous Data.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

An Improved Analysis of Gradient Tracking for Decentralized Machine Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Consensus Control for Decentralized Deep Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free!
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
A Unified Theory of Decentralized SGD with Changing Topology and Local Updates.
Proceedings of the 37th International Conference on Machine Learning, 2020

Decentralized Deep Learning with Arbitrary Communication Compression.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Decentralized Stochastic Optimization and Gossip Algorithms with Compressed Communication.
Proceedings of the 36th International Conference on Machine Learning, 2019

Efficient Greedy Coordinate Descent for Composite Problems.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019


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