• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 32 matches

• 2024
• 
  Mathieu Even, Anastasia Koloskova, Laurent Massoulié:
  Asynchronous SGD on Graphs: a Unified Framework for Asynchronous Decentralized and Federated Optimization. AISTATS 2024: 64-72
• 
  Youssef Allouah, Anastasia Koloskova, Aymane El Firdoussi, Martin Jaggi, Rachid Guerraoui:
  The Privacy Power of Correlated Noise in Decentralized Learning. ICML 2024
• 
  Anastasia Koloskova, Nikita Doikov, Sebastian U. Stich, Martin Jaggi:
  On Convergence of Incremental Gradient for Non-convex Smooth Functions. ICML 2024
• 
  Youssef Allouah, Anastasia Koloskova, Aymane El Firdoussi, Martin Jaggi, Rachid Guerraoui:
  The Privacy Power of Correlated Noise in Decentralized Learning. CoRR abs/2405.01031 (2024)
• 2023
• 
  Anastasia Koloskova, Hadrien Hendrikx, Sebastian U. Stich:
  Revisiting Gradient Clipping: Stochastic bias and tight convergence guarantees. ICML 2023: 17343-17363
• 
  Anastasia Koloskova, Ryan McKenna, Zachary Charles, John Keith Rush, H. Brendan McMahan:
  Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential Privacy. NeurIPS 2023
• 
  Yue Liu, Tao Lin, Anastasia Koloskova, Sebastian U. Stich:
  Decentralized Gradient Tracking with Local Steps. CoRR abs/2301.01313 (2023)
• 
  Anastasia Koloskova, Ryan McKenna, Zachary Charles, Keith Rush, Brendan McMahan:
  Convergence of Gradient Descent with Linearly Correlated Noise and Applications to Differentially Private Learning. CoRR abs/2302.01463 (2023)
• 
  Anastasia Koloskova, Hadrien Hendrikx, Sebastian U. Stich:
  Revisiting Gradient Clipping: Stochastic bias and tight convergence guarantees. CoRR abs/2305.01588 (2023)
• 
  Anastasia Koloskova, Nikita Doikov, Sebastian U. Stich, Martin Jaggi:
  Shuffle SGD is Always Better than SGD: Improved Analysis of SGD with Arbitrary Data Orders. CoRR abs/2305.19259 (2023)
• 
  Mathieu Even, Anastasia Koloskova, Laurent Massoulié:
  Asynchronous SGD on Graphs: a Unified Framework for Asynchronous Decentralized and Federated Optimization. CoRR abs/2311.00465 (2023)
• 2022
• 
  Aleksandr Beznosikov, Pavel E. Dvurechensky, Anastasia Koloskova, Valentin Samokhin, Sebastian U. Stich, Alexander V. Gasnikov:
  Decentralized Local Stochastic Extra-Gradient for Variational Inequalities. NeurIPS 2022
• 
  Anastasia Koloskova, Sebastian U. Stich, Martin Jaggi:
  Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning. NeurIPS 2022
• 
  Anastasia Koloskova, Tao Lin, Sebastian U. Stich:
  An Improved Analysis of Gradient Tracking for Decentralized Machine Learning. CoRR abs/2202.03836 (2022)
• 
  Yatin Dandi, Anastasia Koloskova, Martin Jaggi, Sebastian U. Stich:
  Data-heterogeneity-aware Mixing for Decentralized Learning. CoRR abs/2204.06477 (2022)
• 
  Anastasia Koloskova, Sebastian U. Stich, Martin Jaggi:
  Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning. CoRR abs/2206.08307 (2022)
• 2021
• 
  Dmitry Kovalev, Anastasia Koloskova, Martin Jaggi, Peter Richtárik, Sebastian U. Stich:
  A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free! AISTATS 2021: 4087-4095
• 
  Lingjing Kong, Tao Lin, Anastasia Koloskova, Martin Jaggi, Sebastian U. Stich:
  Consensus Control for Decentralized Deep Learning. ICML 2021: 5686-5696
• 
  Anastasia Koloskova, Tao Lin, Sebastian U. Stich:
  An Improved Analysis of Gradient Tracking for Decentralized Machine Learning. NeurIPS 2021: 11422-11435
• 
  Thijs Vogels, Lie He, Anastasia Koloskova, Sai Praneeth Karimireddy, Tao Lin, Sebastian U. Stich, Martin Jaggi:
  RelaySum for Decentralized Deep Learning on Heterogeneous Data. NeurIPS 2021: 28004-28015
• 
  Lingjing Kong, Tao Lin, Anastasia Koloskova, Martin Jaggi, Sebastian U. Stich:
  Consensus Control for Decentralized Deep Learning. CoRR abs/2102.04828 (2021)
• 
  Aleksandr Beznosikov, Pavel E. Dvurechensky, Anastasia Koloskova, Valentin Samokhin, Sebastian U. Stich, Alexander V. Gasnikov:
  Decentralized Local Stochastic Extra-Gradient for Variational Inequalities. CoRR abs/2106.08315 (2021)
• 
  Thijs Vogels, Lie He, Anastasia Koloskova, Tao Lin, Sai Praneeth Karimireddy, Sebastian U. Stich, Martin Jaggi:
  RelaySum for Decentralized Deep Learning on Heterogeneous Data. CoRR abs/2110.04175 (2021)
• 2020
• 
  Anastasia Koloskova, Tao Lin, Sebastian U. Stich, Martin Jaggi:
  Decentralized Deep Learning with Arbitrary Communication Compression. ICLR 2020
• 
  Anastasia Koloskova, Nicolas Loizou, Sadra Boreiri, Martin Jaggi, Sebastian U. Stich:
  A Unified Theory of Decentralized SGD with Changing Topology and Local Updates. ICML 2020: 5381-5393
• 
  Anastasia Koloskova, Nicolas Loizou, Sadra Boreiri, Martin Jaggi, Sebastian U. Stich:
  A Unified Theory of Decentralized SGD with Changing Topology and Local Updates. CoRR abs/2003.10422 (2020)
• 
  Dmitry Kovalev, Anastasia Koloskova, Martin Jaggi, Peter Richtárik, Sebastian U. Stich:
  A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free! CoRR abs/2011.01697 (2020)
• 2019
• 
  Sai Praneeth Karimireddy, Anastasia Koloskova, Sebastian U. Stich, Martin Jaggi:
  Efficient Greedy Coordinate Descent for Composite Problems. AISTATS 2019: 2887-2896
• 
  Anastasia Koloskova, Sebastian U. Stich, Martin Jaggi:
  Decentralized Stochastic Optimization and Gossip Algorithms with Compressed Communication. ICML 2019: 3478-3487
• 
  Anastasia Koloskova, Sebastian U. Stich, Martin Jaggi:
  Decentralized Stochastic Optimization and Gossip Algorithms with Compressed Communication. CoRR abs/1902.00340 (2019)

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