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ORCIDJames Anderson 0001
Person information
- affiliation: Columbia University, NY, USA
- affiliation (former): California Institute of Technology, Pasadena, CA, USA
- affiliation (PhD 2012): University of Oxford, UK
Other persons with the same name
- James Anderson — disambiguation page
- James Anderson 0002 (aka: James N. Anderson) — University of Edinburgh, UK
- James Anderson 0003 — University of Oklahoma, Norman, OK, USA
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2020 – today
- 2024
[j13]Han Wang, Aritra Mitra, Hamed Hassani, George J. Pappas, James Anderson:
Federated TD Learning with Linear Function Approximation under Environmental Heterogeneity. Trans. Mach. Learn. Res. 2024 (2024)- [c34]Chenyu Zhang, Han Wang, Aritra Mitra, James Anderson:
Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning. ICLR 2024 - [c33]Thomas T. C. K. Zhang, Leonardo Felipe Toso, James Anderson, Nikolai Matni:
Sample-Efficient Linear Representation Learning from Non-IID Non-Isotropic Data. ICLR 2024 - [c32]Leonardo Felipe Toso, Donglin Zhan, James Anderson, Han Wang:
Meta-learning linear quadratic regulators: A policy gradient MAML approach for model-free LQR. L4DC 2024: 902-915 - [c31]Donglin Zhan, Yusheng Dai, Yiwei Dong, Jinghai He, Zhenyi Wang, James Anderson:
Meta-Adaptive Stock Movement Prediction with Two-Stage Representation Learning. SDM 2024: 508-516 - [i39]Leonardo F. Toso, Donglin Zhan, James Anderson
, Han Wang:
Meta-Learning Linear Quadratic Regulators: A Policy Gradient MAML Approach for the Model-free LQR. CoRR abs/2401.14534 (2024) - [i38]Chenyu Zhang, Han Wang, Aritra Mitra, James Anderson:
Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning. CoRR abs/2401.15273 (2024) - [i37]Donglin Zhan, James Anderson:
Data-Efficient and Robust Task Selection for Meta-Learning. CoRR abs/2405.07083 (2024) - [i36]Han Wang, Sihong He, Zhili Zhang, Fei Miao, James Anderson:
Momentum for the Win: Collaborative Federated Reinforcement Learning across Heterogeneous Environments. CoRR abs/2405.19499 (2024) - [i35]Bruce D. Lee, Leonardo F. Toso, Thomas T. C. K. Zhang, James Anderson, Nikolai Matni:
Regret Analysis of Multi-task Representation Learning for Linear-Quadratic Adaptive Control. CoRR abs/2407.05781 (2024) - 2023
- [j12]Carmen Amo Alonso, Jing Shuang Li, James Anderson, Nikolai Matni:
Distributed and Localized Model-Predictive Control-Part I: Synthesis and Implementation. IEEE Trans. Control. Netw. Syst. 10(2): 1058-1068 (2023) - [j11]Carmen Amo Alonso, Jing Shuang Li, Nikolai Matni, James Anderson:
Distributed and Localized Model Predictive Control - Part II: Theoretical Guarantees. IEEE Trans. Control. Netw. Syst. 10(3): 1113-1123 (2023) - [c30]Leonardo F. Toso, Han Wang, James Anderson:
Learning Personalized Models with Clustered System Identification. CDC 2023: 7162-7169 - [c29]Han Wang, Leonardo Felipe Toso, James Anderson:
FedSysID: A Federated Approach to Sample-Efficient System Identification. L4DC 2023: 1308-1320 - [c28]Guangchen Lan, Han Wang, James Anderson, Christopher G. Brinton, Vaneet Aggarwal:
Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updates. NeurIPS 2023 - [c27]Gal Morgenstern, Lital Dabush, Jip Kim, James Anderson, Gil Zussman, Tirza Routtenberg:
Invited Paper: Detection of False Data Injection Attacks in Power Systems Using a Secured-Sensors and Graph-Based Method. SSS 2023: 240-258 - [i34]Han Wang, Aritra Mitra, Hamed Hassani, George J. Pappas, James Anderson:
Federated Temporal Difference Learning with Linear Function Approximation under Environmental Heterogeneity. CoRR abs/2302.02212 (2023) - [i33]Leonardo Felipe Toso, Han Wang, James Anderson:
Learning Personalized Models with Clustered System Identification. CoRR abs/2304.01395 (2023) - [i32]Gal Morgenstern, Jip Kim, James Anderson, Gil Zussman, Tirza Routtenberg:
Protection Against Graph-Based False Data Injection Attacks on Power Systems. CoRR abs/2304.10801 (2023) - [i31]Thomas T. C. K. Zhang, Leonardo Felipe Toso, James Anderson, Nikolai Matni:
Meta-Learning Operators to Optimality from Multi-Task Non-IID Data. CoRR abs/2308.04428 (2023) - [i30]Leonardo Felipe Toso, Han Wang, James Anderson:
Oracle Complexity Reduction for Model-free LQR: A Stochastic Variance-Reduced Policy Gradient Approach. CoRR abs/2309.10679 (2023) - [i29]Guangchen Lan, Han Wang, James Anderson, Christopher G. Brinton, Vaneet Aggarwal:
Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updates. CoRR abs/2310.19807 (2023) - 2022
- [c26]Han Wang, James Anderson:
Large-Scale System Identification Using a Randomized SVD. ACC 2022: 2178-2185 - [c25]Han Wang, Siddartha Marella, James Anderson:
FedADMM: A federated primal-dual algorithm allowing partial participation. CDC 2022: 287-294 - [c24]Yuxiao Chen, Jip Kim, James Anderson:
Distributionally Robust Decision Making Leveraging Conditional Distributions. CDC 2022: 5652-5659 - [c23]Han Wang, James Anderson:
Learning Linear Models Using Distributed Iterative Hessian Sketching. L4DC 2022: 427-440 - [c22]Jip Kim, Siddharth Bhela, James Anderson, Gil Zussman:
Identification of Intraday False Data Injection Attack on DER Dispatch Signals. SmartGridComm 2022: 40-46 - [i28]Carmen Amo Alonso, Jing Shuang Li, Nikolai Matni, James Anderson:
Distributed and Localized Model Predictive Control. Part II: Theoretical Guarantees. CoRR abs/2203.00780 (2022) - [i27]Han Wang, Siddartha Marella, James Anderson:
FedADMM: A Federated Primal-Dual Algorithm Allowing Partial Participation. CoRR abs/2203.15104 (2022) - [i26]Yuxiao Chen, Jip Kim, James Anderson:
Distributionally Robust Decision Making Leveraging Conditional Distributions. CoRR abs/2204.00138 (2022) - [i25]Jip Kim, Siddharth Bhela, James Anderson, Gil Zussman:
Identification of Intraday False Data Injection Attack on DER Dispatch Signals. CoRR abs/2207.03667 (2022) - [i24]Yiqian Wu, Jip Kim, James Anderson:
Mitigation-Aware Bidding Strategies in Electricity Markets. CoRR abs/2211.02766 (2022) - [i23]Han Wang, Leonardo Felipe Toso, James Anderson:
FedSysID: A Federated Approach to Sample-Efficient System Identification. CoRR abs/2211.14393 (2022) - 2021
- [j10]Yuxiao Chen, James Anderson, Karanjit Kalsi, Aaron D. Ames, Steven H. Low:
Safety-Critical Control Synthesis for Network Systems With Control Barrier Functions and Assume-Guarantee Contracts. IEEE Trans. Control. Netw. Syst. 8(1): 487-499 (2021) - [j9]Fengyu Zhou, James Anderson, Steven H. Low:
The Optimal Power Flow Operator: Theory and Computation. IEEE Trans. Control. Netw. Syst. 8(2): 1010-1022 (2021) - [c21]Jing Yu, Yuh-Shyang Wang, James Anderson:
Localized and Distributed H2 State Feedback Control. ACC 2021: 2732-2738 - [i22]Han Wang, James Anderson:
Large-Scale System Identification Using a Randomized SVD. CoRR abs/2109.02703 (2021) - [i21]Han Wang, James Anderson:
Learning Linear Models Using Distributed Iterative Hessian Sketching. CoRR abs/2112.04101 (2021) - 2020
- [c20]James Anderson, Fengyu Zhou, Steven H. Low:
Worst-Case Sensitivity of DC Optimal Power Flow Problems. ACC 2020: 3156-3163 - [c19]Shih-Hao Tseng, James Anderson:
Deployment Architectures for Cyber-Physical Control Systems. ACC 2020: 5287-5294 - [c18]Carmen Amo Alonso, Nikolai Matni, James Anderson:
Explicit Distributed and Localized Model Predictive Control via System Level Synthesis. CDC 2020: 5606-5613 - [i20]James Anderson, Fengyu Zhou, Steven H. Low:
Worst-Case Sensitivity of DC Optimal Power Flow Problems. CoRR abs/2004.01572 (2020) - [i19]Carmen Amo Alonso, Nikolai Matni, James Anderson:
Explicit Distributed and Localized Model Predictive Control via System Level Synthesis. CoRR abs/2005.13807 (2020) - [i18]Jing Yu, Yuh-Shyang Wang, James Anderson:
Localized and Distributed H2 State Feedback Control. CoRR abs/2010.02440 (2020) - [i17]Shih-Hao Tseng, James Anderson:
Synthesis to Deployment: Cyber-Physical Control Architectures. CoRR abs/2012.05211 (2020)
2010 – 2019
- 2019
- [j8]James Anderson, John C. Doyle, Steven H. Low, Nikolai Matni:
System level synthesis. Annu. Rev. Control. 47: 364-393 (2019) - [c17]Yuxiao Chen, James Anderson, Karan Kalsi, Steven H. Low, Aaron D. Ames:
Compositional Set Invariance in Network Systems with Assume-Guarantee Contracts. ACC 2019: 1027-1034 - [c16]Fengyu Zhou, James Anderson, Steven H. Low:
Differential Privacy of Aggregated DC Optimal Power Flow Data. ACC 2019: 1307-1314 - [c15]Yuxiao Chen, James Anderson:
System Level Synthesis with State and Input Constraints. CDC 2019: 5258-5263 - [i16]Yuxiao Chen, James Anderson:
System Level Synthesis with State and Input Constraints. CoRR abs/1903.07174 (2019) - [i15]Fengyu Zhou, James Anderson, Steven H. Low:
Differential Privacy of Aggregated DC Optimal Power Flow Data. CoRR abs/1903.11237 (2019) - [i14]James Anderson, Nikolai Matni, Yuxiao Chen:
Sparsity Preserving Discretization With Error Bounds. CoRR abs/1903.11267 (2019) - [i13]James Anderson, John C. Doyle, Steven H. Low, Nikolai Matni:
System Level Synthesis. CoRR abs/1904.01634 (2019) - [i12]Fengyu Zhou, James Anderson, Steven H. Low:
The Optimal Power Flow Operator: Theory and Computation. CoRR abs/1907.02219 (2019) - [i11]Shih-Hao Tseng, James Anderson:
Deployment Architectures for Cyber-Physical Control Systems. CoRR abs/1911.01510 (2019) - [i10]Yuxiao Chen, James Anderson, Karan Kalsi, Aaron D. Ames, Steven H. Low:
Safety-Critical Control Synthesis for network systems with Control Barrier Functions and Assume-Guarantee Contracts. CoRR abs/1911.03452 (2019) - 2018
- [i9]Yuxiao Chen, James Anderson, Karan Kalsi, Steven H. Low, Aaron D. Ames:
Compositional Set Invariance in Network Systems with Assume-Guarantee Contracts. CoRR abs/1810.10636 (2018) - 2017
- [j7]Giorgio Valmorbida, James Anderson:
Region of attraction estimation using invariant sets and rational Lyapunov functions. Autom. 75: 37-45 (2017) - [j6]Aivar Sootla, James Anderson:
Structured Projection-Based Model Reduction With Application to Stochastic Biochemical Networks. IEEE Trans. Autom. Control. 62(11): 5554-5566 (2017) - [c14]James Anderson, Nikolai Matni:
Structured state space realizations for SLS distributed controllers. Allerton 2017: 982-987 - [c13]John C. Doyle, Nikolai Matni, Yuh Shyang Wang, James Anderson, Steven H. Low:
System level synthesis: A tutorial. CDC 2017: 2856-2867 - [c12]Nikolai Matni, Yuh-Shyang Wang, James Anderson:
Scalable system level synthesis for virtually localizable systems. CDC 2017: 3473-3480 - [c11]James Anderson:
Distance to the nearest stable Metzler matrix. CDC 2017: 6567-6572 - [i8]James Anderson:
Distance to the Nearest Stable Metzler Matrix. CoRR abs/1709.02461 (2017) - 2016
- [j5]Dhruva V. Raman, James Anderson, Antonis Papachristodoulou:
On the performance of nonlinear dynamical systems under parameter perturbation. Autom. 63: 265-273 (2016) - [c10]Dhruva V. Raman, James Anderson, Antonis Papachristodoulou:
A new approach for estimating the robustness of parameter estimates to measurement noise. ACC 2016: 1820-1825 - [c9]Aivar Sootla, James Anderson:
On existence of solutions to structured lyapunov inequalities. ACC 2016: 7013-7018 - [i7]Aivar Sootla, James Anderson:
On Existence of Solutions to Structured Lyapunov Inequalities. CoRR abs/1603.07686 (2016) - [i6]Giorgio Valmorbida, James Anderson:
Region of Attraction Estimation Using Invariant Sets and Rational Lyapunov Functions. CoRR abs/1604.01084 (2016) - 2015
- [j4]Andreas W. K. Harris, James Dolan, Ciaran L. Kelly, James Anderson, Antonis Papachristodoulou:
Designing Genetic Feedback Controllers. IEEE Trans. Biomed. Circuits Syst. 9(4): 475-484 (2015) - [i5]Giorgio Valmorbida, Dhruva V. Raman, James Anderson:
Bounds for Input- and State-to-Output Properties of Uncertain Linear Systems. CoRR abs/1505.05335 (2015) - [i4]Aivar Sootla, James Anderson:
Structured Projection-Based Model Reduction with Application to Stochastic Biochemical Networks. CoRR abs/1510.05784 (2015) - 2014
- [c8]Giorgio Valmorbida, James Anderson:
Region of attraction analysis via invariant sets. ACC 2014: 3591-3596 - [c7]Aivar Sootla, James Anderson:
On projection-based model reduction of biochemical networks part I: The deterministic case. CDC 2014: 3615-3620 - [c6]Aivar Sootla, James Anderson:
On projection-based model reduction of biochemical networks part II: The stochastic case. CDC 2014: 3621-3626 - [i3]Aivar Sootla, James Anderson:
On Projection-Based Model Reduction of Biochemical Networks- Part I: The Deterministic Case. CoRR abs/1403.3579 (2014) - [i2]Aivar Sootla, James Anderson:
On Projection-Based Model Reduction of Biochemical Networks- Part II: The Stochastic Case. CoRR abs/1403.5971 (2014) - 2013
- [i1]Antonis Papachristodoulou, James Anderson, Giorgio Valmorbida, Stephen Prajna, Pete Seiler, Pablo A. Parrilo:
SOSTOOLS Version 3.00 Sum of Squares Optimization Toolbox for MATLAB. CoRR abs/1310.4716 (2013) - 2012
- [j3]James Anderson, Antonis Papachristodoulou:
A Decomposition Technique for Nonlinear Dynamical System Analysis. IEEE Trans. Autom. Control. 57(6): 1516-1521 (2012) - [c5]James Dolan, James Anderson, Antonis Papachristodoulou:
A loop shaping approach for designing biological circuits. CDC 2012: 3614-3619 - 2011
- [j2]James Anderson, Yo-Cheng Chang, Antonis Papachristodoulou:
Model decomposition and reduction tools for large-scale networks in systems biology. Autom. 47(6): 1165-1174 (2011) - [c4]James Anderson, André Teixeira, Henrik Sandberg, Antonis Papachristodoulou:
Dynamical system decomposition using dissipation inequalities. CDC/ECC 2011: 211-216 - 2010
- [c3]James Anderson, Antonis Papachristodoulou:
A network decomposition approach for efficient sum of squares programming based analysis. ACC 2010: 4492-4497 - [c2]Antonis Papachristodoulou, Yo-Cheng Chang, Elias August, James Anderson:
Structured model reduction for dynamical networked systems. CDC 2010: 2670-2675 - [c1]James Anderson, Antonis Papachristodoulou:
Dynamical system decomposition for efficient, sparse analysis. CDC 2010: 6565-6570
2000 – 2009
- 2009
- [j1]James Anderson, Antonis Papachristodoulou:
On validation and invalidation of biological models. BMC Bioinform. 10 (2009)
Coauthor Index
Leonardo F. Toso
aka: Leonardo Felipe Toso
aka: Leonardo Felipe Toso
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