Selected Publications

Control and System Theory

[P9] From Optimization to Control: Quasi Policy Iteration

Amin Kolarijani and Peyman Mohajerin Esfahani
submitted for publication, November 2023, [arXiv]

[C40] Fast Approximate Dynamic Programming for Infinite-Horizon Continuous-State Markov Decision Processes

Amin Kolarijani, Gyula Max, and P. Mohajerin Esfahani
Neural Information Processing Systems (NeurIPS), December 2021, [Link], [arXiv], [Code]
Journal version: [J35], [arXiv], [Code]

[J24] Macroscopic Noisy Bounded Confidence Models with Distributed Radical Opinions

Amin Kolarijani, Anton Proskurnikov, and Peyman Mohajerin Esfahani
IEEE Transactions on Automatic Control (TAC), vol. 66, no. 3, pp. 1174-1189, 2021, [Link], [arXiv]

[J5] A Tractable Fault Detection and Isolation Approach for Nonlinear Systems with Probabilistic Performance

Peyman Mohajerin Esfahani and John Lygeros
IEEE Transactions on Automatic Control (TAC), vol. 61, no. 3, pp. 633-647, March 2016, [Link], [arXiv]

Optimization

[J23] Distributionally Robust Inverse Covariance Estimation: The Wasserstein Shrinkage Estimator

Viet Anh Nguyen, Daniel Kuhn, and Peyman Mohajerin Esfahani
Operations Research (OR), vol. 70, no. 1, pp. 490-515, 2021, [Link], [arXiv], [Code]
>> Winner of the 2018 George Nicholson Outstanding Student Paper

[J14] From Infinite to Finite Programs: Explicit Error Bounds with an Application to Approximate Dynamic Programming

Peyman Mohajerin Esfahani, Tobias Sutter, Daniel Kuhn, and John Lygeros
SIAM Journal on Optimization (SIOPT), vol. 28, no. 3, pp. 1968-1998, July 2018, [Link], [arXiv]

[J15] Data-driven Distributionally Robust Optimization Using the Wasserstein Metric: Performance Guarantees and Tractable Reformulations

Peyman Mohajerin Esfahani and Daniel Kuhn
Mathematical Programming, vol. 171, pp. 115-166, September 2018, [Link], [arXiv]
>> The 2020 INFORMS Frederick W. Lanchester Prize
>> MOSEK Jupyter Notebook and Video

[J3] Performance Bounds for the Scenario Approach and an Extension to a Class of Non-convex Programs

Peyman Mohajerin Esfahani, Tobias Sutter, and John Lygeros
IEEE Transactions on Automatic Control (TAC), vol. 60, no. 1, pp. 46-58, January 2015, [Link], [arXiv]
>> The 2016 George S. Axelby Outstanding Paper Award

Machine Learning

[P5] Learning in Inverse Optimization: Incenter Cost, Augmented Suboptimality Loss, and Algorithms

Pedro Zattoni Scroccaro, Bilge Atasoy, and Peyman Mohajerin Esfahani
submitted for publication, May 2023, [arXiv], [Code]

[J34] Adaptive Online Optimization with Predictions: Static and Dynamic Environments

Pedro Zattoni Scroccaro, Arman Sharifi Kolarijani, and Peyman Mohajerin Esfahani
IEEE Transactions on Automatic Control (TAC), vol. 68, no. 5, pp. 2906-2921, May 2023, [Link], [arXiv]

[C39] Principal Component Hierarchy for Sparse Quadratic Programs

Robbie Vreugdenhil, Viet Anh Nguyen, Armin Eftekhari, Peyman Mohajerin Esfahani
International Conference on Machine Learning (ICML), Vienna, Austria, July 2021, [arXiv], [Code]

[J31] Bridging Bayesian and Minimax Mean Square Error Estimation via Wasserstein Distributionally Robust Optimization

Viet Anh Nguyen, Soroosh Shafieezadeh-Abadeh, Daniel Kuhn, and Peyman Mohajerin Esfahani
Mathematics of Operations Research (MOR), vol. 48, no. 1, pp. 1-37, 2023, [Link], [arXiv]