James Anderson

James Anderson

Columbia University in the City of New York

H-index: 20

North America-United States

About James Anderson

James Anderson, With an exceptional h-index of 20 and a recent h-index of 17 (since 2020), a distinguished researcher at Columbia University in the City of New York, specializes in the field of Control Theory, Nonlinear Systems, Optimization, Machine Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning

Meta-Learning Linear Quadratic Regulators: A Policy Gradient MAML Approach for the Model-free LQR

Asynchronous Heterogeneous Linear Quadratic Regulator Design

Protection against graph-based false data injection attacks on power systems

Control for Societal-scale Challenges: Road Map 2030

Detection of False Data Injection Attacks in Power Systems Using a Secured-Sensors and Graph-Based Method

Distributed and localized model predictive control—Part II: Theoretical guarantees

Oracle Complexity Reduction for Model-free LQR: A Stochastic Variance-Reduced Policy Gradient Approach

James Anderson Information

University

Position

Assistant Professor Electrical Engineering

Citations(all)

1948

Citations(since 2020)

1160

Cited By

1282

hIndex(all)

20

hIndex(since 2020)

17

i10Index(all)

35

i10Index(since 2020)

27

Email

University Profile Page

Columbia University in the City of New York

Google Scholar

View Google Scholar Profile

James Anderson Skills & Research Interests

Control Theory

Nonlinear Systems

Optimization

Machine Learning

Top articles of James Anderson

Title

Journal

Author(s)

Publication Date

Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning

arXiv preprint arXiv:2401.15273

Chenyu Zhang

Han Wang

Aritra Mitra

James Anderson

2024/1/27

Meta-Learning Linear Quadratic Regulators: A Policy Gradient MAML Approach for the Model-free LQR

arXiv preprint arXiv:2401.14534

Leonardo F Toso

Donglin Zhan

James Anderson

Han Wang

2024/1/25

Asynchronous Heterogeneous Linear Quadratic Regulator Design

arXiv preprint arXiv:2404.09061

Leonardo F Toso

Han Wang

James Anderson

2024/4/13

Protection against graph-based false data injection attacks on power systems

IEEE Transactions on Control of Network Systems

Gal Morgenstern

Jip Kim

James Anderson

Gil Zussman

Tirza Routtenberg

2024/2/29

Control for Societal-scale Challenges: Road Map 2030

Andrew Alleyne

Frank Allgöwer

Aaron Ames

Saurabh Amin

James Anderson

...

2023/5

Detection of False Data Injection Attacks in Power Systems Using a Secured-Sensors and Graph-Based Method

2020/3/10

Distributed and localized model predictive control—Part II: Theoretical guarantees

IEEE Transactions on Control of Network Systems

Carmen Amo Alonso

Jing Shuang Li

Nikolai Matni

James Anderson

2023/3/28

Oracle Complexity Reduction for Model-free LQR: A Stochastic Variance-Reduced Policy Gradient Approach

arXiv preprint arXiv:2309.10679

Leonardo F Toso

Han Wang

James Anderson

2023/9/19

Federated Temporal Difference Learning with Linear Function Approximation under Environmental Heterogeneity

arXiv preprint arXiv:2302.02212

Han Wang

Aritra Mitra

Hamed Hassani

George J Pappas

James Anderson

2023/2/4

Model-free Learning with Heterogeneous Dynamical Systems: A Federated LQR Approach

arXiv preprint arXiv:2308.11743

Han Wang

Leonardo F Toso

Aritra Mitra

James Anderson

2023/8/22

Learning Personalized Models with Clustered System Identification

Leonardo F Toso

Han Wang

James Anderson

2023/12/13

Mitigation-aware bidding strategies in electricity markets

Yiqian Wu

Jip Kim

James Anderson

2023/7/16

Sample-Efficient Linear Representation Learning from Non-IID Non-Isotropic Data

Thomas TCK Zhang

Leonardo Felipe Toso

James Anderson

Nikolai Matni

2023/10/13

Fedsysid: A federated approach to sample-efficient system identification

Han Wang

Leonardo Felipe Toso

James Anderson

2023/6/6

Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updates

arXiv preprint arXiv:2310.19807

Guangchen Lan

Han Wang

James Anderson

Christopher Brinton

Vaneet Aggarwal

2023/10/9

Meta-Adaptive Stock Movement Prediction with Two-Stage Representation Learning

Donglin Zhan

Yusheng Dai

Yiwei Dong

Jinghai He

Zhenyi Wang

...

2022/11

Identification of Intraday False Data Injection Attack on DER Dispatch Signals

Jip Kim

Siddharth Bhela

James Anderson

Gil Zussman

2022/10/25

Large-scale system identification using a randomized svd

Han Wang

James Anderson

2022/6/8

Learning Linear Models Using Distributed Iterative Hessian Sketching

Han Wang

James Anderson

2022/5/11

Distributionally Robust Decision Making Leveraging Conditional Distributions

Yuxiao Chen

Jip Kim

James Anderson

2022/12/6

See List of Professors in James Anderson University(Columbia University in the City of New York)

Co-Authors

H-index: 103
John Doyle

John Doyle

California Institute of Technology

H-index: 95
Steven H. Low

Steven H. Low

California Institute of Technology

H-index: 62
Aaron D. Ames

Aaron D. Ames

California Institute of Technology

H-index: 53
Antonis Papachristodoulou

Antonis Papachristodoulou

University of Oxford

H-index: 49
Mauricio Barahona

Mauricio Barahona

Imperial College London

H-index: 47
Peter Seiler Jr

Peter Seiler Jr

University of Michigan-Dearborn

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