Publications
Publications
Accepted/Published
Alizadeh, Z*., Jalilzadeh, A., and Yousefian, F., “Randomized Lagrangian Stochastic Approximation for Large-Scale Constrained Stochastic Nash Games”. Published in Optimization Letters, 2024.
Jalilzadeh, A., and Yousefian, F., Ebrahimi M., “Stochastic Approximation for Estimating the Price of Stability in Stochastic Nash Games”. Published in ACM Transactions on Modeling and Computer Simulation, 2024.
Gubbi, K. I., Latibari, B. S., Chowdhury, M. A., Jalilzadeh, A., Yazdandoost Hamedani, E., Rafatirad, S., Sasan, A., Homayoun, H., and Salehi, S., “Optimized and Automated Secure IC Design Flow: A Defense-in-Depth Approach”. Published in IEEE Transactions on Circuits and Systems, 2024.
Flores, O., Anani, A., Li, H., and Jalilzadeh, A. “Optimizing Transition: Investigating the Influence of Operational Parameters on Production Scheduling Optimization for Mines Transitioning from Open Pit to Block Caving Methods”. Published in Optimization and Engineering, 2024.
Anani, A., Flores, O., Li, H., and Jalilzadeh, A. “Heuristic and Exact Approaches to Optimize the Production Scheduling of Mines Transitioning from Open Pit to Block Caving”. Published in Mining, Metallurgy & Exploration, 2024.
Yazdandoost Hamedani, E., Jalilzadeh, A. “A Stochastic Variance-reduced Accelerated Primal-dual Method for Finite-sum Saddle-point Problems”. Published in Computational Optimization and Applications, 2023.
Bardakci I. e., Jalilzadeh A., Lagoa C., and Shanbhag U. V., “Probability Maximization via MinkowskiFunctionals: Convex Representations and Tractable Resolution”. Published in Mathematical Programming, 2022.
Jalilzadeh A., Shanbhag U. V., Blanchet H., and Glynn P., “Optimal Smoothed Variable Sample-size Accelerated Proximal Methods for Structured Nonsmooth Stochastic Convex Programs”. Published in Stochastic Systems, 2022.
Jalilzadeh, A. “Primal-Dual Incremental Gradient Method for Nonsmooth and Convex Optimization Problems”. Published in Optimization Letters, 2021.
Jalilzadeh, A., Nedich A., Shanbhag, U. V., and Yousefian, F., “A Variable Sample-size Stochastic Quasi-NewtonMethod for Smooth and Nonsmooth Stochastic Convex Optimization”. Published in Mathematics of Operations Research, 2021.
Jalilzadeh A., Lei J., and Shanbhag U. V., “Open Problem-Iterative Schemes for Stochastic Optimization: Convergence Statements and Limit Theorems”. Published in Stochastic Systems 9.3 (2019): 299-302.
Under Review
Alizadeh, Z*., Yazdandoost Hamedani, E., and Jalilzadeh, A., “Variance-reduction for Variational Inequality Problems with Bregman Distance Function”. arXiv:2405.10735.
Alizadeh, Z*., and Jalilzadeh, A., “Convergence Analysis of Non-Strongly-Monotone Stochastic Quasi-Variational Inequalities”. arXiv:2401.03076.
Yazdandoost Hamedani, E., Jalilzadeh, A., and Aybat, N. S., “A Randomized Block-Coordinate Primal-Dual Method for
Large-scale Stochastic Saddle Point Problems”. arXiv:1907.03886v5
Farsi, A*., Alizadeh, Z*., and Jalilzadeh, A., “Solving Distributionally Robust Nash Games: Algorithm Development and Convergence Analysis”.
Melcher, C., Jalilzadeh, A., Yazdandoost Hamedani, E., “Linear Convergence of a Unified Primal-Dual Algorithm for Convex-Concave Saddle Point Problems with Quadratic Growth”.
Alizadeh, Z.* and Jalilzadeh, A., "Stochastic Quasi-Variational Inequalities: Convergence Analysis Beyond Strong Monotonicity" Optimization for Machine Learning Workshop, NeurIPS 2024.
Boroun, M.*, Yazdandoost Hamedani, E., and Jalilzadeh, A. "Projection-Free Methods for Solving Nonconvex-Concave Saddle Point Problems". Neural Information Processing Systems (NeurIPS) 2023.
Yazdandoost Hamedani, E., Jalilzadeh, A., and Aybat, N. S., "Randomized Primal-Dual Methods with Adaptive Step Sizes." International Conference on Artificial Intelligence and Statistics. PMLR, 2023.
U. Talwar*, A. Jalilzadeh, and M. Kupinski, "Semi-Supervised Adaptation of a Channelized Quadratic Observer" in Optica Latin America Optics and Photonics Conference (LAOP) 2024, Technical Digest Series (Optica Publishing Group, 2024), paper Tu4A.22.
Alizadeh, Z.*, Polanco, F. P.**, and Jalilzadeh, A., "A Projection-Based Algorithm for Solving Stochastic Inverse Variational Inequality Problems". 2023 Winter Simulation Conference (WSC), San Antonio, TX, USA, 2023, pp. 3532-3540.
Boroun, M.,*, Alizadeh, Z.*, and A. Jalilzadeh, "Accelerated Primal-dual Scheme for a Class of Stochastic Nonconvex-concave Saddle Point Problems," 2023 American Control Conference (ACC), San Diego, CA, USA, 2023, pp. 204-209.
N. Abolfazli, A. Jalilzadeh, and E. Y. Hamedani, "An Accelerated Asynchronous Distributed Method for Convex Constrained Optimization Problems," 2023 57th Annual Conference on Information Sciences and Systems (CISS), Baltimore, MD, USA, 2023, pp. 1-6
Alizadeh, Z.*, Otero, B. M.**, and Jalilzadeh, A. “An Inexact Variance-Reduced Method For Stochastic Quasi-Variational Inequality Problems With An Application In Healthcare”. In Proceedings of the 2022 Winter Simulation Conference (WSC), Singapore.
Boroun, M.*, Jalilzadeh, A. “Inexact-Proximal Accelerated Gradient Method for Stochastic Nonconvex Constrained Optimization Problems”. In Proceedings of the 2021 Winter Simulation Conference, Phoenix, AZ.
Jalilzadeh, A., and Shanbhag, U. V. (2019) “A Proximal-point Algorithm with Variable Sample-sizes (PPAWSS)for Monotone Stochastic Variational Inequality Problems”, In Proceedings of the 2019 Winter SimulationConference, National Harbor, MD.
Jalilzadeh, A., Nedich, A., Shanbhag, U. V., and Yousefian, F. (2018) “A Variable Sample-size Stochastic Quasi-Newton Method for Smooth and Nonsmooth Stochastic Convex Optimization”, In 2018 IEEE Conference on Decision and Control (CDC) pp. 4097-4102. IEEE.
Jalilzadeh, A., and Shanbhag, U. V. (2016) “eg-VSSA: an extragradient variable sample-size stochastic approximation scheme: error analysis and complexity trade-offs”, In 2016 Winter Simulation Conference (WSC), pp. 690-701. IEEE.
Jalilzadeh, A. (2023). Stochastic Quasi-NewtonScheme. In: Pardalos, P.M., Prokopyev, O.A. (eds) Encyclopedia of Optimization. Springer, Cham. https://doi.org/10.1007/978-3-030-54621-2_830-1