Approximate level method

von Richtárik, Peter
Veröffentlicht 2008

STOCHASTIC SIGN DESCENT METHODS: NEW ALGORITHMS AND BETTER THEORY

von SAFARYAN, MHER
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 12 of 16 (2022)

CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression

von Li, Zhize
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 17 of 36 (2022)

PRIMAL DUAL INTERPRETATION OF THE PROXIMAL STOCHASTIC GRADIENT LANGEVIN ALGORITHM

von Salim, Adil
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 5 of 27 (2021)

EF21: A New, Simpler, Theoretically Better, and Practically Faster Error Feedback

von Richtarik, Peter
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 6 of 36 (2022)

Accelerated Primal-Dual Gradient Method for Smooth and Convex-Concave Saddle-Point Problems with Bilinear Coupling

von Kovalev, Dmitry
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 28 of 50 (2023)

Variance Reduced ProxSkip: Algorithm, Theory and Application to Federated Learning

von Malinovsky, Grigory
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 20 of 50 (2023)

OPTIMAL AND PRACTICAL ALGORITHMS FOR SMOOTH AND STRONGLY CONVEX DECENTRALIZED OPTIMIZATION

von Kovalev, Dmitry
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 22 of 27 (2021)

DISTRIBUTED SECOND ORDER METHODS WITH FAST RATES AND COMPRESSED COMMUNICATION

von ISLAMOV, RUSTEM
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 6 of 16 (2022)

Error Compensated Distributed SGD Can Be Accelerated

von Qian, Xun
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 36 of 36 (2022)

Matrix completion under interval uncertainty

von Mareček, Jakub
Veröffentlicht in European journal of operational research (12017)

99% OF WORKER-MASTER COMMUNICATION IN DISTRIBUTED OPTIMIZATION IS NOT NEEDED

von MISHCHENKO, KONSTANTIN
Veröffentlicht in Conference on Uncertainty in Artificial Intelligence (36. : 2020 : Online) 36th Conference on Uncertainty in Artificial Intelligence (UAI 2020) ; Volume 3 of 3 (2021)

STOCHASTIC PROXIMAL LANGEVIN ALGORITHM: POTENTIAL SPLITTING AND NONASYMPTOTIC RATES

von Salim, Adil
Veröffentlicht in NeurIPS (33. : 2019 : Vancouver, British Columbia) 32nd Conference on Neural Information Processing Systems (NeurIPS 2019) ; Volume 9 of 20 (2020)

A Convergence Theory for SVGD in the Population Limit Under Talagrand’s Inequality T1

von Salim, Adil
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 23 of 33 (2023)

Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox

von Sadiev, Abdurakhmon
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 29 of 50 (2023)

Smoothness Matrices Beat Smoothness Constants: Better Communication Compression Techniques for Distributed Optimization

von Safaryan, Mher
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 31 of 36 (2022)

Proximal and Federated Random Reshuffling

von Mishchenko, Konstantin
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 19 of 33 (2023)

EF-BV: A Unified Theory of Error Feedback and Variance Reduction Mechanisms for Biased and Unbiased Compression in Distributed Optimization

von Condat, Laurent
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 23 of 50 (2023)

Theoretically Better and Numerically Faster Distributed Optimization with Smoothness-Aware Quantization Techniques

von Wang, Bokun
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 13 of 50 (2023)

RANDOM RESHUFFLING: SIMPLE ANALYSIS WITH VAST IMPROVEMENTS

von Mishchenko, Konstantin
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 21 of 27 (2021)