Published/Accepted

Woojin Jung, Saeed Ghadimi, Dimitrios Ntarlagiannis, and Andrew H. Kim, “Using AI/ML to Evaluate the Distribution of Community Development Aid Across Myanmar”, ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO'23), to appear.

Zhaoqi Leng, Pranav Mundada, Saeed Ghadimi, and Andrew Houck “Efficient Algorithms for High-Dimensional Quantum Optimal Control of a Transmon Qubit”, Physical Review Applied 19 (2023).

Saeed Ghadimi and Warren Powell, “Stochastic Search for a Parametric Cost Function Approximation: Energy storage with rolling forecasts”, European Journal of Operational Research 312( 2023), 641-652.
Tesi Xiao, Xuxing Chen, Krishnakumar Balasubramanian, Saeed Ghadimi"A One-Sample Decentralized Proximal Algorithm for Non-Convex Stochastic Composite Optimization", UAI (2023).

Krishnakumar Balasubramanian, Saeed Ghadimi, and Anthony Nguyen, "Stochastic Multi-level Composition Optimization Algorithms with Level-Independent Convergence Rates", SIAM Journal on Optimization 32 (2022), 519-544.

Abhishek Roy, Krishnakumar Balasubramanian, Saeed Ghadimi, and Prasant Mohapatra,  “ Stochastic Zeroth-Order Optimization under Nonstationary  and Nonconvexity”, Journal of Machine Learning Research 23 (2022), 1-47.

Tesi Xiao, Krishnakumar Balasubramanian,  and Saeed Ghadimi , "Improved Complexities for Stochastic Conditional Gradient Methods under Interpolation-like Conditions", Operations Research Letters, 50 (2022), 184-189.

Abhishek Roy, Lingqing Shen, Krishna Balasubramanian, and Saeed Ghadimi, “Stochastic Zeroth-order Discretizations of Langevin Diffusions for Bayesian Inference”,  Bernoulli 28 (2022), 1810-1834.

Krishna Balasubramanian and Saeed Ghadimi, “Zeroth-order Nonconvex Stochastic Optimization: Handling Constraints, High-Dimensionality, and Saddle-Points”, Foundations of Computational Mathematics 22 (2022), 35-76.

Abhishek Roy, Krishnakumar Balasubramanian, and  Saeed Ghadimi, "Projection-free Constrained Stochastic Nonconvex Optimization with State-dependent Markov Data", NeurIPS (2022). 

Tesi Xiao, Krishnakumar Balasubramanian, Saeed Ghadimi, "A Projection-free Algorithm for Constrained Multi-level Stochastic Composition Optimization", NeurIPS (2022).

Abhishek Roy, Krishnakumar Balasubramanian, Saeed Ghadimi, and Prasant Mohapatra, ``Escaping Saddle-Points Faster under Interpolation-like Conditions'', NeurIPS (2020).

Saeed Ghadimi, Andrzej Ruszczynski, and Mengdi Wang, “A Single Time-Scale Stochastic Approximation Method for Nested Stochastic Optimization”. SIAM Journal on Optimization (2020): 30(1), 960–979 .

Saeed Ghadimi, Guanghui Lan, and Hongchao Zhang, “Generalized Uniformly Optimal Methods for Nonlinear Programming”. Journal of Scientific Computing (2019): 79, 1854–1881.  

Krishna Balasubramanian, and Saeed Ghadimi, “Zeroth-order (Non)-Convex Stochastic Optimization via Conditional Gradient and Gradient Updates”. NeurIPS (2018). 

Saeed Ghadimi, “Conditional Gradient Type Methods for Composite Nonlinear and Stochastic Optimization”. Mathematical Programming (2019): 173, 431–464. 

Saeed Ghadimi, Hongchao Zhang, and Guanghui Lan, “Mini-batch Stochastic Approximation Methods for Nonconvex Stochastic Composite Optimization”. Mathematical Programming (2016):155, 267-305. 

Saeed Ghadimi and Guanghui Lan, “Accelerated Gradient Methods for Nonconvex Nonlinear and Stochastic Programming”. Mathematical Programming (2016): 156, 59-99. 

Reza Zanjirani Farahani, W Y Szeto, and Saeed Ghadimi, “The Single Facility Location Problem with Time-dependent Weights and Relocation Cost Over a Continuous Time Horizon”. Journal of the Operational Research Society (2014): 66(2), 1-13.  

 Saeed Ghadimi, Ferenc Szidarovszky, Reza Zanjirani Farahani, and Alireza yousefzadeh Khiabani, “Coordination of Advertising in Supply Management with Cooperating Manufacturer and Retailers”. IMA Journal of Management Mathematics (2013): 24(1), 1-19. 

Saeed Ghadimi and Guanghui Lan, “Optimal Stochastic Approximation Algorithms for Strongly Convex Stochastic Composite Optimization, II: Shrinking Procedures and Optimal Algorithms”. SIAM Journal on Optimization (2013): 23(4), 2061-2089. 

Saeed Ghadimi and Guanghui Lan, “Stochastic First- and Zeroth-order Methods for NonconvexStochastic Programming”. SIAM Journal on Optimization (2013): 23(4), 2341-2368. 

Saeed Ghadimi and Guanghui Lan, “Optimal Stochastic Approximation Algorithms for Strongly Convex Stochastic Composite Optimization, I: a Generic Algorithmic Framework”. SIAM Journal on Optimization (2012): 22(4), 1469-1492.