Stochastic Gradient Descent under Markovian Sampling Schemes

28 February 2023

Papers citing "Stochastic Gradient Descent under Markovian Sampling Schemes"

23 / 23 papers shown

Title
Achieving Tighter Finite-Time Rates for Heterogeneous Federated Stochastic Approximation under Markovian Sampling Feng Zhu Aritra Mitra Robert W. Heath FedML 36 0 0 15 Apr 2025
$Online Learning Algorithms in Hilbert Spaces with $\beta-$ and $\phi-$Mixing Sequences$ Online Learning Algorithms in Hilbert Spaces with $\beta-$ and $\phi-$ Mixing Sequences Priyanka Roy Susanne Saminger-Platz 39 0 0 05 Feb 2025
Scalable Decentralized Learning with Teleportation Yuki Takezawa Sebastian U. Stich 64 1 0 25 Jan 2025
Boosting Asynchronous Decentralized Learning with Model Fragmentation Sayan Biswas Anne-Marie Kermarrec Alexis Marouani Rafael Pires Rishi Sharma M. Vos 25 1 0 16 Oct 2024
Long-Context Linear System Identification Oğuz Kaan Yüksel Mathieu Even Nicolas Flammarion 26 0 0 08 Oct 2024
Debiasing Federated Learning with Correlated Client Participation Zhenyu Sun Ziyang Zhang Zheng Xu Gauri Joshi Pranay Sharma Ermin Wei FedML 29 0 0 02 Oct 2024
Does Worst-Performing Agent Lead the Pack? Analyzing Agent Dynamics in Unified Distributed SGD Jie Hu Yi-Ting Ma Do Young Eun FedML 27 0 0 26 Sep 2024
The Entrapment Problem in Random Walk Decentralized Learning Zonghong Liu S. E. Rouayheb Matthew Dwyer 21 1 0 30 Jul 2024
Stochastic Optimization Algorithms for Instrumental Variable Regression with Streaming Data Xuxing Chen Abhishek Roy Yifan Hu Krishnakumar Balasubramanian 43 1 0 29 May 2024
Beyond Noise: Privacy-Preserving Decentralized Learning with Virtual Nodes Sayan Biswas Mathieu Even Anne-Marie Kermarrec Laurent Massoulie Rafael Pires Rishi Sharma M. Vos 46 3 0 15 Apr 2024
Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling Arman Adibi Nicolò Dal Fabbro Luca Schenato Sanjeev R. Kulkarni H. Vincent Poor George J. Pappas Hamed Hassani A. Mitra 35 8 0 19 Feb 2024
Differentially Private Decentralized Learning with Random Walks Edwige Cyffers A. Bellet Jalaj Upadhyay FedML 36 2 0 12 Feb 2024
Accelerating Distributed Stochastic Optimization via Self-Repellent Random Walks Jie Hu Vishwaraj Doshi Do Young Eun 50 2 0 18 Jan 2024
Central Limit Theorem for Two-Timescale Stochastic Approximation with Markovian Noise: Theory and Applications Jie Hu Vishwaraj Doshi Do Young Eun 38 4 0 17 Jan 2024
Stochastic optimization with arbitrary recurrent data sampling William G. Powell Hanbaek Lyu 37 0 0 15 Jan 2024
Asynchronous SGD on Graphs: a Unified Framework for Asynchronous Decentralized and Federated Optimization Mathieu Even Anastasia Koloskova Laurent Massoulié FedML 43 13 0 01 Nov 2023
On Convergence of Incremental Gradient for Non-Convex Smooth Functions Anastasia Koloskova N. Doikov Sebastian U. Stich Martin Jaggi 36 2 0 30 May 2023
First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities Aleksandr Beznosikov S. Samsonov Marina Sheshukova Alexander Gasnikov A. Naumov Eric Moulines 46 14 0 25 May 2023
Self-Repellent Random Walks on General Graphs -- Achieving Minimal Sampling Variance via Nonlinear Markov Chains Vishwaraj Doshi Jie Hu Do Young Eun 27 4 0 08 May 2023
Streaming PCA for Markovian Data Syamantak Kumar Purnamrita Sarkar 50 6 0 03 May 2023
FLEX: an Adaptive Exploration Algorithm for Nonlinear Systems Matthieu Blanke Marc Lelarge 31 4 0 26 Apr 2023
Adapting to Mixing Time in Stochastic Optimization with Markovian Data Ron Dorfman Kfir Y. Levy 37 28 0 09 Feb 2022
Asynchronous speedup in decentralized optimization Mathieu Even Hadrien Hendrikx Laurent Massoulie 26 4 0 07 Jun 2021