ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2211.14393
  4. Cited By
FedSysID: A Federated Approach to Sample-Efficient System Identification

FedSysID: A Federated Approach to Sample-Efficient System Identification

25 November 2022
Han Wang
Leonardo F. Toso
James Anderson
    FedML
ArXivPDFHTML

Papers citing "FedSysID: A Federated Approach to Sample-Efficient System Identification"

11 / 11 papers shown
Title
A State Alignment-Centric Approach to Federated System Identification: The FedAlign Framework
A State Alignment-Centric Approach to Federated System Identification: The FedAlign Framework
Ertuğrul Keçeci
Müjde Güzelkaya
Tufan Kumbasar
FedML
Presented at ResearchTrend Connect | FedML on 23 Apr 2025
105
0
0
15 Mar 2025
A survey on secure decentralized optimization and learning
A survey on secure decentralized optimization and learning
Changxin Liu
Nicola Bastianello
Wei Huo
Yang Shi
Karl H. Johansson
26
1
0
16 Aug 2024
Combining Federated Learning and Control: A Survey
Combining Federated Learning and Control: A Survey
Jakob Weber
Markus Gurtner
A. Lobe
Adrian Trachte
Andreas Kugi
FedML
AI4CE
26
2
0
12 Jul 2024
Joint Learning of Linear Dynamical Systems under Smoothness Constraints
Joint Learning of Linear Dynamical Systems under Smoothness Constraints
Hemant Tyagi
26
0
0
03 Jun 2024
Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement
  Learning
Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning
Chenyu Zhang
Han Wang
Aritra Mitra
James Anderson
21
18
0
27 Jan 2024
Meta-Learning Linear Quadratic Regulators: A Policy Gradient MAML
  Approach for Model-free LQR
Meta-Learning Linear Quadratic Regulators: A Policy Gradient MAML Approach for Model-free LQR
Leonardo F. Toso
Donglin Zhan
James Anderson
Han Wang
26
9
0
25 Jan 2024
Improved Communication Efficiency in Federated Natural Policy Gradient
  via ADMM-based Gradient Updates
Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updates
Guangchen Lan
Han Wang
James Anderson
Christopher G. Brinton
Vaneet Aggarwal
FedML
19
27
0
09 Oct 2023
Robot Fleet Learning via Policy Merging
Robot Fleet Learning via Policy Merging
Lirui Wang
Kaiqing Zhang
Allan Zhou
Max Simchowitz
Russ Tedrake
42
4
0
02 Oct 2023
Meta-Learning Operators to Optimality from Multi-Task Non-IID Data
Meta-Learning Operators to Optimality from Multi-Task Non-IID Data
Thomas T. Zhang
Leonardo F. Toso
James Anderson
Nikolai Matni
67
13
0
08 Aug 2023
Learning Personalized Models with Clustered System Identification
Learning Personalized Models with Clustered System Identification
Leonardo F. Toso
Hang Wang
James Anderson
19
9
0
03 Apr 2023
Linear Convergence in Federated Learning: Tackling Client Heterogeneity
  and Sparse Gradients
Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients
A. Mitra
Rayana H. Jaafar
George J. Pappas
Hamed Hassani
FedML
55
157
0
14 Feb 2021
1