Analysis of Biased Stochastic Gradient Descent Using Sequential Semidefinite Programs

3 November 2017

Papers citing "Analysis of Biased Stochastic Gradient Descent Using Sequential Semidefinite Programs"

7 / 7 papers shown

Title
DYNAFED: Tackling Client Data Heterogeneity with Global Dynamics Renjie Pi Weizhong Zhang Yueqi Xie Jiahui Gao Xiaoyu Wang Sunghun Kim Qifeng Chen DD 39 26 0 20 Nov 2022
Tradeoffs between convergence rate and noise amplification for momentum-based accelerated optimization algorithms Hesameddin Mohammadi Meisam Razaviyayn Mihailo R. Jovanović 31 7 0 24 Sep 2022
Exact Formulas for Finite-Time Estimation Errors of Decentralized Temporal Difference Learning with Linear Function Approximation Xing-ming Guo Bin Hu 13 2 0 20 Apr 2022
Convex Programs and Lyapunov Functions for Reinforcement Learning: A Unified Perspective on the Analysis of Value-Based Methods Xing-ming Guo Bin Hu OffRL 27 3 0 14 Feb 2022
On the Convergence of SGD with Biased Gradients Ahmad Ajalloeian Sebastian U. Stich 6 84 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
A frequency-domain analysis of inexact gradient methods Oran Gannot 24 25 0 31 Dec 2019