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Hesameddin Mohammadi

Check here for my arXiv preprints.

Journal Articles

  1. Convergence and sample complexity of gradient methods for the model-free linear-quadratic regulator problem.
    By Mohammadi, H., Zare, A., Soltanolkotabi, M. and Jovanović, M.R.
    In IEEE Trans. Automat. Control, vol. 67, no. 5, pp. 2435–2450, May 2022.
    bibtex entry @article{mohzarsoljovTAC22, author = {Mohammadi, H. and Zare, A. and Soltanolkotabi, M. and Jovanovi\'c, M. R.}, title = {Convergence and sample complexity of gradient methods for the model-free linear-quadratic regulator problem}, journal = {IEEE Trans. Automat. Control}, volume = {67}, number = {5}, pages = {2435-2450}, month = may, year = {2022}, pdf = {https://ieeexplore.ieee.org/abstract/document/9448427} }
    link.   pdf.

  2. Transient growth of accelerated optimization algorithms.
    By Mohammadi, H., Samuelson, S. and Jovanović, M.R.
    In IEEE Trans. Automat. Control (doi:10.1109/TAC.2022.3162154), 2022.
    bibtex entry @article{mohsamjovTAC22, author = {Mohammadi, H. and Samuelson, S. and Jovanovi\'c, M. R.}, title = {Transient growth of accelerated optimization algorithms}, journal = {IEEE Trans. Automat. Control (doi:10.1109/TAC.2022.3162154)}, year = {2022}, pdf = {https://ieeexplore.ieee.org/abstract/document/9741291} }
    link.   pdf.

  3. Computing stabilizing feedback gains via a model-free policy gradient.
    By Ozaslan, I.K., Mohammadi, H. and Jovanović, M.R.
    In IEEE Control Syst. Lett., pp. 407–412, 2022.
    bibtex entry @article{ozamohjovLCSS22, author = {Ozaslan, I. K. and Mohammadi, H. and Jovanovi\'c, M. R.}, title = {Computing stabilizing feedback gains via a model-free policy gradient}, journal = {IEEE Control Syst. Lett.}, year = {2022}, pages = {407-412}, pdf = {https://ieeexplore.ieee.org/document/9814885} }
    link.   pdf.

  4. Tradeoffs between convergence rate and noise amplification for momentum-based accelerated optimization algorithms.
    By Mohammadi, H., Razaviyayn, M. and Jovanović, M.R.
    In IEEE Trans. Automat. Control, 2022.
    bibtex entry @article{mohrazjov2022, author = {Mohammadi, H. and Razaviyayn, M. and Jovanovi\'c, M. R.}, title = {Tradeoffs between convergence rate and noise amplification for momentum-based accelerated optimization algorithms}, journal = {IEEE Trans. Automat. Control}, note = {(UNDER REVIEW)}, year = {2022}, pdf = {https://arxiv.org/abs/2209.11920} }
    link.

  5. Robustness of accelerated first-order algorithms for strongly convex optimization problems.
    By Mohammadi, H., Razaviyayn, M. and Jovanović, M.R.
    In IEEE Trans. Automat. Control, vol. 66, no. 6, pp. 2480–2495, Jun. 2021.
    bibtex entry @article{mohrazjovTAC21, author = {Mohammadi, H. and Razaviyayn, M. and Jovanovi\'c, M. R.}, title = {Robustness of accelerated first-order algorithms for strongly convex optimization problems}, journal = {IEEE Trans. Automat. Control}, volume = {66}, number = {6}, pages = {2480-2495}, month = jun, year = {2021}, pdf = {https://ieeexplore.ieee.org/abstract/document/9137636} }
    link.   pdf.

  6. On the linear convergence of random search for discrete-time LQR.
    By Mohammadi, H., Soltanolkotabi, M. and Jovanović, M.R.
    In IEEE Control Syst. Lett., vol. 5, no. 3, pp. 989–994, Jul. 2021.
    bibtex entry @article{mohsoljovLCSS21, author = {Mohammadi, H. and Soltanolkotabi, M. and Jovanovi\'c, M. R.}, title = {On the linear convergence of random search for discrete-time {LQR}}, journal = {IEEE Control Syst. Lett.}, volume = {5}, number = {3}, pages = {989-994}, month = jul, year = {2021}, pdf = {https://ieeexplore.ieee.org/abstract/document/9130755} }
    link.   pdf.

  7. Proximal algorithms for large-scale statistical modeling and sensor/actuator selection.
    By Zare, A., Mohammadi, H., Dhingra, N.K., Georgiou, T.T. and Jovanović, M.R.
    In IEEE Trans. Automat. Control, vol. 65, no. 8, pp. 3441–3456, Aug. 2020.
    bibtex entry @article{zarmohdhigeojovTAC20, author = {Zare, A. and Mohammadi, H. and Dhingra, N. K. and Georgiou, T. T. and Jovanovi\'c, M. R.}, title = {Proximal algorithms for large-scale statistical modeling and sensor/actuator selection}, journal = {IEEE Trans. Automat. Control}, volume = {65}, number = {8}, pages = {3441-3456}, month = aug, year = {2020}, pdf = {https://ieeexplore.ieee.org/abstract/document/8876689} }
    link.   pdf.

Conference Articles

  1. Noise amplification of momentum-based optimization algorithms.
    By Mohammadi, H., Razaviyayn, M. and Jovanović, M.R.
    In Proceedings of the 2023 American Control Conference (SUBMITTED), San Diego, CA2023.
    bibtex entry @inproceedings{mohrazjovACC23, author = {Mohammadi, H. and Razaviyayn, M. and Jovanovi\'c, M. R.}, title = {Noise amplification of momentum-based optimization algorithms}, booktitle = {Proceedings of the 2023 American Control Conference (SUBMITTED)}, year = {2023}, address = {San Diego, CA} }

  2. Performance of noisy higher-order accelerated gradient flow dynamics for strongly convex quadratic optimization problems.
    By Samuelson, S., Mohammadi, H. and Jovanović, M.R.
    In Proceedings of the 2023 American Control Conference (SUBMITTED), San Diego, CA2023.
    bibtex entry @inproceedings{sammohjovACC23, author = {Samuelson, S. and Mohammadi, H. and Jovanovi\'c, M. R.}, title = {Performance of noisy higher-order accelerated gradient flow dynamics for strongly convex quadratic optimization problems}, booktitle = {Proceedings of the 2023 American Control Conference (SUBMITTED)}, year = {2023}, address = {San Diego, CA} }

  3. On the noise amplification of primal-dual gradient flow dynamics based on proximal augmented Lagrangian.
    By Mohammadi, H. and Jovanović, M.R.
    In Proceedings of the 2022 American Control Conference, Atlanta, GA, pp. 926–931, 2022.
    bibtex entry @inproceedings{mohjovACC22, author = {Mohammadi, H. and Jovanovi\'c, M. R.}, title = {On the noise amplification of primal-dual gradient flow dynamics based on proximal augmented {L}agrangian}, booktitle = {Proceedings of the 2022 American Control Conference}, pages = {926-931}, year = {2022}, address = {Atlanta, GA}, pdf = {https://ieeexplore.ieee.org/document/9867147} }
    link.

  4. On the lack of gradient domination for linear quadratic Gaussian problems with incomplete state information.
    By Mohammadi, H., Soltanolkotabi, M. and Jovanović, M.R.
    In Proceedings of the 60th IEEE Conference on Decision and Control, Austin, TX, pp. 1120–1124, 2021.
    bibtex entry @inproceedings{mohsoljovCDC21, author = {Mohammadi, H. and Soltanolkotabi, M. and Jovanovi\'c, M. R.}, booktitle = {Proceedings of the 60th IEEE Conference on Decision and Control}, title = {On the lack of gradient domination for linear quadratic Gaussian problems with incomplete state information}, year = {2021}, address = {Austin, TX}, pages = {1120-1124}, pdf = {https://ieeexplore.ieee.org/document/9683369} }
    link.

  5. Random search for learning the linear quadratic regulator.
    By Mohammadi, H., Soltanolkotabi, M. and Jovanović, M.R.
    In Proceedings of the 2020 American Control Conference, Denver, CO, pp. 4798–4803, 2020.
    bibtex entry @inproceedings{mohsoljovACC20, author = {Mohammadi, H. and Soltanolkotabi, M. and Jovanovi\'c, M. R.}, title = {Random search for learning the linear quadratic regulator}, booktitle = {Proceedings of the 2020 American Control Conference}, pages = {4798-4803}, year = {2020}, address = {Denver, CO}, pdf = {https://ieeexplore.ieee.org/document/9147749} }
    link.

  6. Transient growth of accelerated first-order methods.
    By Samuelson, S., Mohammadi, H. and Jovanović, M.R.
    In Proceedings of the 2020 American Control Conference, Denver, CO, pp. 2858–2863, 2020.
    bibtex entry @inproceedings{sammohjovACC20, author = {Samuelson, S. and Mohammadi, H. and Jovanovi\'c, M. R.}, title = {Transient growth of accelerated first-order methods}, booktitle = {Proceedings of the 2020 American Control Conference}, pages = {2858-2863}, year = {2020}, address = {Denver, CO}, pdf = {https://ieeexplore.ieee.org/abstract/document/9147427} }
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  7. Learning the model-free linear quadratic regulator via random search.
    By Mohammadi, H., Soltanolkotabi, M. and Jovanović, M.R.
    In Proceedings of Machine Learning Research, 2nd Annual Conference on Learning for Dynamics and Control, Berkeley, CAvol. 120, , pp. 1–9, 2020.
    bibtex entry @inproceedings{mohsoljovL4DC20, author = {Mohammadi, H. and Soltanolkotabi, M. and Jovanovi\'c, M. R.}, title = {Learning the model-free linear quadratic regulator via random search}, booktitle = {Proceedings of Machine Learning Research, 2nd Annual Conference on Learning for Dynamics and Control}, volume = {120}, pages = {1-9}, year = {2020}, address = {Berkeley, CA}, pdf = {https://proceedings.mlr.press/v120/mohammadi20a.html} }
    link.

  8. On the transient growth of Nesterov’s accelerated method for strongly convex optimization problems.
    By Samuelson, S., Mohammadi, H. and Jovanović, M.R.
    In Proceedings of the 59th IEEE Conference on Decision and Control, Jeju Island, Republic of Korea, pp. 5911–5916, 2020.
    bibtex entry @inproceedings{sammohjovCDC20, author = {Samuelson, S. and Mohammadi, H. and Jovanovi\'c, M. R.}, booktitle = {Proceedings of the 59th IEEE Conference on Decision and Control}, title = {On the transient growth of {N}esterov's accelerated method for strongly convex optimization problems}, year = {2020}, address = {Jeju Island, Republic of Korea}, pages = {5911-5916}, pdf = {https://ieeexplore.ieee.org/document/9304412} }
    link.

  9. Performance of noisy Nesterov’s accelerated method for strongly convex optimization problems.
    By Mohammadi, H., Razaviyayn, M. and Jovanović, M.R.
    In Proceedings of the 2019 American Control Conference, Philadelphia, PA, pp. 3426–3431, 2019.
    bibtex entry @inproceedings{mohrazjovACC19, author = {Mohammadi, H. and Razaviyayn, M. and Jovanovi\'c, M. R.}, booktitle = {Proceedings of the 2019 American Control Conference}, title = {Performance of noisy {N}esterov's accelerated method for strongly convex optimization problems}, year = {2019}, address = {Philadelphia, PA}, pages = {3426-3431}, pdf = {https://ieeexplore.ieee.org/abstract/document/8814680} }
    link.

  10. Global exponential convergence of gradient methods over the nonconvex landscape of the linear quadratic regulator.
    By Mohammadi, H., Zare, A., Soltanolkotabi, M. and Jovanović, M.R.
    In Proceedings of the 58th IEEE Conference on Decision and Control, Nice, France, pp. 7474–7479, 2019.
    bibtex entry @inproceedings{mohzarsoljovCDC19, author = {Mohammadi, H. and Zare, A. and Soltanolkotabi, M. and Jovanovi\'c, M. R.}, booktitle = {Proceedings of the 58th IEEE Conference on Decision and Control}, title = {Global exponential convergence of gradient methods over the nonconvex landscape of the linear quadratic regulator}, year = {2019}, address = {Nice, France}, pages = {7474-7479}, pdf = {https://ieeexplore.ieee.org/document/9029985} }
    link.

  11. Combining SOS with Branch and Bound to Isolate Global Solutions of Polynomial Optimization Problems.
    By Colbert, B., Mohammadi, H. and Peet, M.M.
    In Proceedings of the 2018 American Control Conference, Milwaukee, WI, pp. 2190–2197, 2018.
    bibtex entry @inproceedings{colmohpeeACC18, author = {{Colbert}, B. and {Mohammadi}, H. and {Peet}, M. M.}, booktitle = {Proceedings of the 2018 American Control Conference}, title = {Combining SOS with Branch and Bound to Isolate Global Solutions of Polynomial Optimization Problems}, year = {2018}, address = {Milwaukee, WI}, pages = {2190-2197}, pdf = {https://ieeexplore.ieee.org/document/8431203} }
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  12. On the stability of gradient flow dynamics for a rank-one matrix approximation problem.
    By Mohammadi, H., Razaviyayn, M. and Jovanović, M.R.
    In Proceedings of the 2018 American Control Conference, Milwaukee, WI, pp. 4533–4538, 2018.
    bibtex entry @inproceedings{mohrazjovACC18, author = {Mohammadi, H. and Razaviyayn, M. and Jovanovi\'c, M. R.}, booktitle = {Proceedings of the 2018 American Control Conference}, title = {On the stability of gradient flow dynamics for a rank-one matrix approximation problem}, year = {2018}, address = {Milwaukee, WI}, pages = {4533-4538}, pdf = {https://ieeexplore.ieee.org/document/8431227} }
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  13. Variance amplification of accelerated first-order algorithms for strongly convex quadratic optimization problems.
    By Mohammadi, H., Razaviyayn, M. and Jovanović, M.R.
    In Proceedings of the 57th IEEE Conference on Decision and Control, Miami, FL, pp. 5753–5758, 2018.
    bibtex entry @inproceedings{mohrazjovCDC18, author = {Mohammadi, H. and Razaviyayn, M. and Jovanovi\'c, M. R.}, title = {Variance amplification of accelerated first-order algorithms for strongly convex quadratic optimization problems}, booktitle = {Proceedings of the 57th IEEE Conference on Decision and Control}, year = {2018}, address = {Miami, FL}, pages = {5753-5758}, pdf = {https://ieeexplore.ieee.org/document/8619183} }
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  14. Estimating the region of attraction using polynomial optimization: A converse Lyapunov result.
    By Jones, M., Mohammadi, H. and Peet, M.M.
    In Proceedings of the 56th IEEE Conference on Decision and Control, Melbourne, Australia, pp. 1796–1802, 2017.
    bibtex entry @inproceedings{jonmohpeeCDC17, author = {{Jones}, M. and {Mohammadi}, H. and {Peet}, M. M.}, booktitle = {Proceedings of the 56th IEEE Conference on Decision and Control}, title = {Estimating the region of attraction using polynomial optimization: A converse Lyapunov result}, year = {2017}, address = {Melbourne, Australia}, pages = {1796-1802}, pdf = {https://ieeexplore.ieee.org/abstract/document/8263908} }
    link.

Book Chapters

  1. Model-free linear quadratic regulator.
    By Mohammadi, H., Soltanolkotabi, M. and Jovanović, M.R.
    In Handbook on RL and Control,
    Springer Studies in Systems, Decision and Control, 2020, pp. pp. 173–185
    bibtex entry @incollection{mohsoljov20book, title = {Model-free linear quadratic regulator}, author = {Mohammadi, H. and Soltanolkotabi, M. and Jovanovi\'c, M. R.}, booktitle = {Handbook on RL and Control}, pages = {173-185}, year = {2020}, publisher = {Springer Studies in Systems, Decision and Control}, pdf = {https://link.springer.com/chapter/10.1007/978-3-030-60990-0_6} }
    link.