Koloskova, Anastasia

13 publications

ICML 2025 Certified Unlearning for Neural Networks Anastasia Koloskova, Youssef Allouah, Animesh Jha, Rachid Guerraoui, Sanmi Koyejo

AISTATS 2024 Asynchronous SGD on Graphs: A Unified Framework for Asynchronous Decentralized and Federated Optimization Mathieu Even, Anastasia Koloskova, Laurent Massoulie

ICML 2024 On Convergence of Incremental Gradient for Non-Convex Smooth Functions Anastasia Koloskova, Nikita Doikov, Sebastian U Stich, Martin Jaggi

ICML 2024 The Privacy Power of Correlated Noise in Decentralized Learning Youssef Allouah, Anastasia Koloskova, Aymane El Firdoussi, Martin Jaggi, Rachid Guerraoui

ICML 2023 Revisiting Gradient Clipping: Stochastic Bias and Tight Convergence Guarantees Anastasia Koloskova, Hadrien Hendrikx, Sebastian U Stich

NeurIPSW 2022 Data-Heterogeneity-Aware Mixing for Decentralized Learning Yatin Dandi, Anastasia Koloskova, Martin Jaggi, Sebastian U Stich

NeurIPSW 2022 Decentralized Stochastic Optimization with Client Sampling Ziwei Liu, Anastasia Koloskova, Martin Jaggi, Tao Lin

AISTATS 2021 A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free! Dmitry Kovalev, Anastasia Koloskova, Martin Jaggi, Peter Richtarik, Sebastian Stich

ICML 2021 Consensus Control for Decentralized Deep Learning Lingjing Kong, Tao Lin, Anastasia Koloskova, Martin Jaggi, Sebastian Stich

ICML 2020 A Unified Theory of Decentralized SGD with Changing Topology and Local Updates Anastasia Koloskova, Nicolas Loizou, Sadra Boreiri, Martin Jaggi, Sebastian Stich

ICLR 2020 Decentralized Deep Learning with Arbitrary Communication Compression Anastasia Koloskova, Tao Lin, Sebastian U. Stich, Martin Jaggi

ICML 2019 Decentralized Stochastic Optimization and Gossip Algorithms with Compressed Communication Anastasia Koloskova, Sebastian Stich, Martin Jaggi

AISTATS 2019 Efficient Greedy Coordinate Descent for Composite Problems Sai Praneeth Karimireddy, Anastasia Koloskova, Sebastian U. Stich, Martin Jaggi