Hesameddin Mohammadi

Publication Activity (10 Years)

Years Active: 2017-2023
Publications (10 Years): 25

Top Topics

Linear Quadratic

Optimization Problems

Top Venues

IEEE Trans. Autom. Control.

Publications

Hesameddin Mohammadi, Samantha Samuelson, Mihailo R. Jovanovic
Transient Growth of Accelerated Optimization Algorithms. IEEE Trans. Autom. Control. 68 (3) (2023)
Hesameddin Mohammadi, Meisam Razaviyayn, Mihailo R. Jovanovic
Noise amplifiation of momentum-based optimization algorithms. ACC (2023)
Samantha Samuelson, Hesameddin Mohammadi, Mihailo R. Jovanovic
Performance of Noisy Three-Step Accelerated First-Order Optimization Algorithms for Strongly Convex Quadratic Problems. CDC (2023)
Ibrahim Kurban Özaslan, Hesameddin Mohammadi, Mihailo R. Jovanovic
Computing Stabilizing Feedback Gains via a Model-Free Policy Gradient Method. IEEE Control. Syst. Lett. 7 (2023)
Samantha Samuelson, Hesameddin Mohammadi, Mihailo R. Jovanovic
Performance of noisy higher-order accelerated gradient flow dynamics for strongly convex quadratic optimization problems. ACC (2023)
Hesameddin Mohammadi, Meisam Razaviyayn, Mihailo R. Jovanovic
Tradeoffs between convergence rate and noise amplification for momentum-based accelerated optimization algorithms. CoRR (2022)
Hesameddin Mohammadi, Mihailo R. Jovanovic
On the noise amplification of primal-dual gradient flow dynamics based on proximal augmented Lagrangian. ACC (2022)
Hesameddin Mohammadi, Armin Zare, Mahdi Soltanolkotabi, Mihailo R. Jovanovic
Convergence and Sample Complexity of Gradient Methods for the Model-Free Linear-Quadratic Regulator Problem. IEEE Trans. Autom. Control. 67 (5) (2022)
Hesameddin Mohammadi, Meisam Razaviyayn, Mihailo R. Jovanovic
Robustness of Accelerated First-Order Algorithms for Strongly Convex Optimization Problems. IEEE Trans. Autom. Control. 66 (6) (2021)
Hesameddin Mohammadi, Samantha Samuelson, Mihailo R. Jovanovic
Transient growth of accelerated first-order methods for strongly convex optimization problems. CoRR (2021)
Hesameddin Mohammadi, Mahdi Soltanolkotabi, Mihailo R. Jovanovic
On the Linear Convergence of Random Search for Discrete-Time LQR. IEEE Control. Syst. Lett. 5 (3) (2021)
Hesameddin Mohammadi, Mahdi Soltanolkotabi, Mihailo R. Jovanovic
On the lack of gradient domination for linear quadratic Gaussian problems with incomplete state information. CDC (2021)
Samantha Samuelson, Hesameddin Mohammadi, Mihailo R. Jovanovic
On the transient growth of Nesterov's accelerated method for strongly convex optimization problems. CDC (2020)
Hesameddin Mohammadi, Mihailo R. Jovanovic, Mahdi Soltanolkotabi
Learning the model-free linear quadratic regulator via random search. L4DC (2020)
Hesameddin Mohammadi, Mahdi Soltanolkotabi, Mihailo R. Jovanovic
Random search for learning the linear quadratic regulator. ACC (2020)
Samantha Samuelson, Hesameddin Mohammadi, Mihailo R. Jovanovic
Transient growth of accelerated first-order methods. ACC (2020)
Armin Zare, Hesameddin Mohammadi, Neil K. Dhingra, Tryphon T. Georgiou, Mihailo R. Jovanovic
Proximal Algorithms for Large-Scale Statistical Modeling and Sensor/Actuator Selection. IEEE Trans. Autom. Control. 65 (8) (2020)
Hesameddin Mohammadi, Armin Zare, Mahdi Soltanolkotabi, Mihailo R. Jovanovic
Global exponential convergence of gradient methods over the nonconvex landscape of the linear quadratic regulator. CDC (2019)
Hesameddin Mohammadi, Meisam Razaviyayn, Mihailo R. Jovanovic
Performance of noisy Nesterov's accelerated method for strongly convex optimization problems. ACC (2019)
Hesameddin Mohammadi, Armin Zare, Mahdi Soltanolkotabi, Mihailo R. Jovanovic
Convergence and sample complexity of gradient methods for the model-free linear quadratic regulator problem. CoRR (2019)
Hesameddin Mohammadi, Meisam Razaviyayn, Mihailo R. Jovanovic
Robustness of accelerated first-order algorithms for strongly convex optimization problems. CoRR (2019)
Hesameddin Mohammadi, Meisam Razaviyayn, Mihailo R. Jovanovic
Variance Amplification of Accelerated First-Order Algorithms for Strongly Convex Quadratic Optimization Problems. CDC (2018)
Brendon K. Colbert, Hesameddin Mohammadi, Matthew M. Peet
Combining SOS with Branch and Bound to Isolate Global Solutions of Polynomial Optimization Problems. ACC (2018)
Hesameddin Mohammadi, Meisam Razaviyayn, Mihailo R. Jovanovic
On the stability of gradient flow dynamics for a rank-one matrix approximation problem. ACC (2018)
Morgan Jones, Hesameddin Mohammadi, Matthew M. Peet
Estimating the region of attraction using polynomial optimization: A converse Lyapunov result. CDC (2017)