Tight Dimension Independent Lower Bound on the Expected Convergence Rate
for Diminishing Step Sizes in SGD

Tight Dimension Independent Lower Bound on the Expected Convergence Rate for Diminishing Step Sizes in SGD

10 October 2018

Phuong Ha Nguyen

Marten van Dijk

Papers citing "Tight Dimension Independent Lower Bound on the Expected Convergence Rate for Diminishing Step Sizes in SGD"

11 / 11 papers shown

Title
Variance Reduction Methods Do Not Need to Compute Full Gradients: Improved Efficiency through Shuffling Daniil Medyakov Gleb Molodtsov S. Chezhegov Alexey Rebrikov Aleksandr Beznosikov 105 0 0 21 Feb 2025
Momentum Aggregation for Private Non-convex ERM Hoang Tran Ashok Cutkosky 28 14 0 12 Oct 2022
Towards Noise-adaptive, Problem-adaptive (Accelerated) Stochastic Gradient Descent Sharan Vaswani Benjamin Dubois-Taine Reza Babanezhad 51 11 0 21 Oct 2021
Hogwild! over Distributed Local Data Sets with Linearly Increasing Mini-Batch Sizes Marten van Dijk Nhuong V. Nguyen Toan N. Nguyen Lam M. Nguyen Quoc Tran-Dinh Phuong Ha Nguyen FedML 42 10 0 27 Oct 2020
Lower Bounds and Optimal Algorithms for Personalized Federated Learning Filip Hanzely Slavomír Hanzely Samuel Horváth Peter Richtárik FedML 50 186 0 05 Oct 2020
Asynchronous Federated Learning with Reduced Number of Rounds and with Differential Privacy from Less Aggregated Gaussian Noise Marten van Dijk Nhuong V. Nguyen Toan N. Nguyen Lam M. Nguyen Quoc Tran-Dinh Phuong Ha Nguyen FedML 16 28 0 17 Jul 2020
Random Reshuffling: Simple Analysis with Vast Improvements Konstantin Mishchenko Ahmed Khaled Peter Richtárik 37 131 0 10 Jun 2020
Better Theory for SGD in the Nonconvex World Ahmed Khaled Peter Richtárik 13 179 0 09 Feb 2020
Stochastic gradient descent for hybrid quantum-classical optimization R. Sweke Frederik Wilde Johannes Jakob Meyer Maria Schuld Paul K. Fährmann Barthélémy Meynard-Piganeau Jens Eisert 17 236 0 02 Oct 2019
New Convergence Aspects of Stochastic Gradient Algorithms Lam M. Nguyen Phuong Ha Nguyen Peter Richtárik K. Scheinberg Martin Takáč Marten van Dijk 23 66 0 10 Nov 2018
Lower error bounds for the stochastic gradient descent optimization algorithm: Sharp convergence rates for slowly and fast decaying learning rates Arnulf Jentzen Philippe von Wurstemberger 75 31 0 22 Mar 2018