Anastasia Koloskova

36 papers A* 13A 3Journal 20

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Certified Unlearning for Neural Networks. ICML Anastasia Koloskova, Youssef Allouah, Animesh Jha, Rachid Guerraoui, Sanmi Koyejo
2025	J	`jnl`	Certified Unlearning for Neural Networks. CoRR Anastasia Koloskova, Youssef Allouah, Animesh Jha, Rachid Guerraoui, Sanmi Koyejo
2025	J	`jnl`	Decentralized gradient tracking with local steps. Optim. Methods Softw. Yue Liu, Tao Lin, Anastasia Koloskova, Sebastian U. Stich
2025	J	`jnl`	FedMuon: Federated Learning with Bias-corrected LMO-based Optimization. CoRR Yuki Takezawa, Anastasia Koloskova, Xiaowen Jiang, Sebastian U. Stich
2024	A	`conf`	Asynchronous SGD on Graphs: a Unified Framework for Asynchronous Decentralized and Federated Optimization. AISTATS Mathieu Even, Anastasia Koloskova, Laurent Massoulié
2024	A*	`conf`	On Convergence of Incremental Gradient for Non-convex Smooth Functions. ICML Anastasia Koloskova, Nikita Doikov, Sebastian U. Stich, Martin Jaggi
2024	A*	`conf`	The Privacy Power of Correlated Noise in Decentralized Learning. ICML Youssef Allouah, Anastasia Koloskova, Aymane El Firdoussi, Martin Jaggi, Rachid Guerraoui
2024	J	`jnl`	The Privacy Power of Correlated Noise in Decentralized Learning. CoRR Youssef Allouah, Anastasia Koloskova, Aymane El Firdoussi, Martin Jaggi, Rachid Guerraoui
2023	J	`jnl`	Asynchronous SGD on Graphs: a Unified Framework for Asynchronous Decentralized and Federated Optimization. CoRR Mathieu Even, Anastasia Koloskova, Laurent Massoulié
2023	J	`jnl`	Convergence of Gradient Descent with Linearly Correlated Noise and Applications to Differentially Private Learning. CoRR Anastasia Koloskova, Ryan McKenna, Zachary Charles, Keith Rush, Brendan McMahan
2023	J	`jnl`	Decentralized Gradient Tracking with Local Steps. CoRR Yue Liu, Tao Lin, Anastasia Koloskova, Sebastian U. Stich
2023	A*	`conf`	Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential Privacy. NeurIPS Anastasia Koloskova, Ryan McKenna, Zachary Charles, John Keith Rush, H. Brendan McMahan
2023	A*	`conf`	Revisiting Gradient Clipping: Stochastic bias and tight convergence guarantees. ICML Anastasia Koloskova, Hadrien Hendrikx, Sebastian U. Stich
2023	J	`jnl`	Revisiting Gradient Clipping: Stochastic bias and tight convergence guarantees. CoRR Anastasia Koloskova, Hadrien Hendrikx, Sebastian U. Stich
2023	J	`jnl`	Shuffle SGD is Always Better than SGD: Improved Analysis of SGD with Arbitrary Data Orders. CoRR Anastasia Koloskova, Nikita Doikov, Sebastian U. Stich, Martin Jaggi
2022	J	`jnl`	An Improved Analysis of Gradient Tracking for Decentralized Machine Learning. CoRR Anastasia Koloskova, Tao Lin, Sebastian U. Stich
2022	J	`jnl`	Data-heterogeneity-aware Mixing for Decentralized Learning. CoRR Yatin Dandi, Anastasia Koloskova, Martin Jaggi, Sebastian U. Stich
2022	A*	`conf`	Decentralized Local Stochastic Extra-Gradient for Variational Inequalities. NeurIPS Aleksandr Beznosikov, Pavel E. Dvurechensky, Anastasia Koloskova, Valentin Samokhin, Sebastian U. Stich, Alexander V. Gasnikov
2022	A*	`conf`	Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning. NeurIPS Anastasia Koloskova, Sebastian U. Stich, Martin Jaggi
2022	J	`jnl`	Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning. CoRR Anastasia Koloskova, Sebastian U. Stich, Martin Jaggi
2021	A	`conf`	A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free! AISTATS Dmitry Kovalev, Anastasia Koloskova, Martin Jaggi, Peter Richtárik, Sebastian U. Stich
2021	A*	`conf`	An Improved Analysis of Gradient Tracking for Decentralized Machine Learning. NeurIPS Anastasia Koloskova, Tao Lin, Sebastian U. Stich
2021	A*	`conf`	Consensus Control for Decentralized Deep Learning. ICML Lingjing Kong, Tao Lin, Anastasia Koloskova, Martin Jaggi, Sebastian U. Stich
2021	J	`jnl`	Consensus Control for Decentralized Deep Learning. CoRR Lingjing Kong, Tao Lin, Anastasia Koloskova, Martin Jaggi, Sebastian U. Stich
2021	J	`jnl`	Decentralized Local Stochastic Extra-Gradient for Variational Inequalities. CoRR Aleksandr Beznosikov, Pavel E. Dvurechensky, Anastasia Koloskova, Valentin Samokhin, Sebastian U. Stich, Alexander V. Gasnikov
2021	A*	`conf`	RelaySum for Decentralized Deep Learning on Heterogeneous Data. NeurIPS Thijs Vogels, Lie He, Anastasia Koloskova, Sai Praneeth Karimireddy, Tao Lin, Sebastian U. Stich, Martin Jaggi
2021	J	`jnl`	RelaySum for Decentralized Deep Learning on Heterogeneous Data. CoRR Thijs Vogels, Lie He, Anastasia Koloskova, Tao Lin, Sai Praneeth Karimireddy, Sebastian U. Stich, Martin Jaggi
2020	J	`jnl`	A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free! CoRR Dmitry Kovalev, Anastasia Koloskova, Martin Jaggi, Peter Richtárik, Sebastian U. Stich
2020	A*	`conf`	A Unified Theory of Decentralized SGD with Changing Topology and Local Updates. ICML Anastasia Koloskova, Nicolas Loizou, Sadra Boreiri, Martin Jaggi, Sebastian U. Stich
2020	J	`jnl`	A Unified Theory of Decentralized SGD with Changing Topology and Local Updates. CoRR Anastasia Koloskova, Nicolas Loizou, Sadra Boreiri, Martin Jaggi, Sebastian U. Stich
2020	A*	`conf`	Decentralized Deep Learning with Arbitrary Communication Compression. ICLR Anastasia Koloskova, Tao Lin, Sebastian U. Stich, Martin Jaggi
2019	J	`jnl`	Decentralized Deep Learning with Arbitrary Communication Compression. CoRR Anastasia Koloskova, Tao Lin, Sebastian U. Stich, Martin Jaggi
2019	A*	`conf`	Decentralized Stochastic Optimization and Gossip Algorithms with Compressed Communication. ICML Anastasia Koloskova, Sebastian U. Stich, Martin Jaggi
2019	J	`jnl`	Decentralized Stochastic Optimization and Gossip Algorithms with Compressed Communication. CoRR Anastasia Koloskova, Sebastian U. Stich, Martin Jaggi
2019	A	`conf`	Efficient Greedy Coordinate Descent for Composite Problems. AISTATS Sai Praneeth Karimireddy, Anastasia Koloskova, Sebastian U. Stich, Martin Jaggi
2018	J	`jnl`	Efficient Greedy Coordinate Descent for Composite Problems. CoRR Sai Praneeth Karimireddy, Anastasia Koloskova, Sebastian U. Stich, Martin Jaggi