Stochastic Gradient Descent with Biased but Consistent Gradient Estimators

31 July 2018

Papers citing "Stochastic Gradient Descent with Biased but Consistent Gradient Estimators"

12 / 12 papers shown

Title
Graph Neural Preconditioners for Iterative Solutions of Sparse Linear Systems Jie Chen AI4CE 59 2 0 28 Jan 2025
Behind the Myth of Exploration in Policy Gradients Adrien Bolland Gaspard Lambrechts Damien Ernst 56 0 0 31 Jan 2024
Generalizing Gaussian Smoothing for Random Search Katelyn Gao Ozan Sener 29 14 0 27 Nov 2022
Learning from time-dependent streaming data with online stochastic algorithms Antoine Godichon-Baggioni Nicklas Werge Olivier Wintenberger 31 3 0 25 May 2022
Gaussian Process Inference Using Mini-batch Stochastic Gradient Descent: Convergence Guarantees and Empirical Benefits Hao Chen Lili Zheng Raed Al Kontar Garvesh Raskutti 20 3 0 19 Nov 2021
Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining Tim Kaler Nickolas Stathas Anne Ouyang A. Iliopoulos Tao B. Schardl C. E. Leiserson Jie Chen GNN 70 53 0 16 Oct 2021
Privacy Amplification for Federated Learning via User Sampling and Wireless Aggregation Mohamed Seif Wei-Ting Chang Ravi Tandon FedML 23 45 0 02 Mar 2021
On the Convergence of SGD with Biased Gradients Ahmad Ajalloeian Sebastian U. Stich 6 83 0 31 Jul 2020
Biased Stochastic First-Order Methods for Conditional Stochastic Optimization and Applications in Meta Learning Yifan Hu Siqi Zhang Xin Chen Niao He ODL 41 55 0 25 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
Adaptively Truncating Backpropagation Through Time to Control Gradient Bias Christopher Aicher N. Foti E. Fox MQ 22 32 0 17 May 2019
A simpler approach to obtaining an O(1/t) convergence rate for the projected stochastic subgradient method Simon Lacoste-Julien Mark W. Schmidt Francis R. Bach 128 259 0 10 Dec 2012