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ORCIDSaeed Ghadimi
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2020 – today
- 2024
[j15]Saeed Ghadimi
, Warren B. Powell:
Stochastic search for a parametric cost function approximation: Energy storage with rolling forecasts. Eur. J. Oper. Res. 312(2): 641-652 (2024)- [j14]Alireza Aghasi, Saeed Ghadimi, Yue Xing, MohammadJavad Feizollahi:
An Adversarially Robust Formulation of Linear Regression With Missing Data. IEEE Trans. Signal Process. 72: 4950-4966 (2024) - [i13]Alireza Aghasi, Saeed Ghadimi:
Fully Zeroth-Order Bilevel Programming via Gaussian Smoothing. CoRR abs/2404.00158 (2024) - 2023
- [c5]Tesi Xiao, Xuxing Chen, Krishnakumar Balasubramanian, Saeed Ghadimi:
A one-sample decentralized proximal algorithm for non-convex stochastic composite optimization. UAI 2023: 2324-2334 - [i12]Tesi Xiao, Xuxing Chen, Krishnakumar Balasubramanian, Saeed Ghadimi:
A One-Sample Decentralized Proximal Algorithm for Non-Convex Stochastic Composite Optimization. CoRR abs/2302.09766 (2023) - [i11]Leila Khalatbari, Yejin Bang, Dan Su, Willy Chung, Saeed Ghadimi, Hossein Sameti, Pascale Fung:
Learn What NOT to Learn: Towards Generative Safety in Chatbots. CoRR abs/2304.11220 (2023) - [i10]Xuxing Chen, Krishnakumar Balasubramanian, Saeed Ghadimi:
Stochastic Nested Compositional Bi-level Optimization for Robust Feature Learning. CoRR abs/2307.05384 (2023) - 2022
- [j13]Krishnakumar Balasubramanian, Saeed Ghadimi:
Zeroth-Order Nonconvex Stochastic Optimization: Handling Constraints, High Dimensionality, and Saddle Points. Found. Comput. Math. 22(1): 35-76 (2022) - [j12]Abhishek Roy, Krishnakumar Balasubramanian, Saeed Ghadimi, Prasant Mohapatra:
Stochastic Zeroth-Order Optimization under Nonstationarity and Nonconvexity. J. Mach. Learn. Res. 23: 64:1-64:47 (2022) - [j11]Tesi Xiao, Krishnakumar Balasubramanian, Saeed Ghadimi:
Improved complexities for stochastic conditional gradient methods under interpolation-like conditions. Oper. Res. Lett. 50(2): 184-189 (2022) - [j10]Krishnakumar Balasubramanian, Saeed Ghadimi, Anthony Nguyen:
Stochastic Multilevel Composition Optimization Algorithms with Level-Independent Convergence Rates. SIAM J. Optim. 32(2): 519-544 (2022) - [c4]Abhishek Roy, Krishnakumar Balasubramanian, Saeed Ghadimi:
Constrained Stochastic Nonconvex Optimization with State-dependent Markov Data. NeurIPS 2022 - [c3]Tesi Xiao, Krishnakumar Balasubramanian, Saeed Ghadimi:
A Projection-free Algorithm for Constrained Stochastic Multi-level Composition Optimization. NeurIPS 2022 - [i9]Warren B. Powell, Saeed Ghadimi:
The Parametric Cost Function Approximation: A new approach for multistage stochastic programming. CoRR abs/2201.00258 (2022) - [i8]Alireza Aghasi, MohammadJavad Feizollahi, Saeed Ghadimi:
RIGID: Robust Linear Regression with Missing Data. CoRR abs/2205.13635 (2022) - [i7]Abhishek Roy, Krishnakumar Balasubramanian, Saeed Ghadimi:
Projection-free Constrained Stochastic Nonconvex Optimization with State-dependent Markov Data. CoRR abs/2206.11346 (2022) - 2020
- [j9]Saeed Ghadimi, Andrzej Ruszczynski, Mengdi Wang:
A Single Timescale Stochastic Approximation Method for Nested Stochastic Optimization. SIAM J. Optim. 30(1): 960-979 (2020) - [c2]Abhishek Roy, Krishnakumar Balasubramanian, Saeed Ghadimi, Prasant Mohapatra:
Escaping Saddle-Point Faster under Interpolation-like Conditions. NeurIPS 2020 - [i6]Tesi Xiao, Krishnakumar Balasubramanian, Saeed Ghadimi:
Improved Complexities for Stochastic Conditional Gradient Methods under Interpolation-like Conditions. CoRR abs/2006.08167 (2020) - [i5]Krishnakumar Balasubramanian, Saeed Ghadimi, Anthony Nguyen:
Stochastic Multi-level Composition Optimization Algorithms with Level-Independent Convergence Rates. CoRR abs/2008.10526 (2020) - [i4]Abhishek Roy, Krishnakumar Balasubramanian, Saeed Ghadimi, Prasant Mohapatra:
Escaping Saddle-Points Faster under Interpolation-like Conditions. CoRR abs/2009.13016 (2020)
2010 – 2019
- 2019
- [j8]Saeed Ghadimi, Guanghui Lan, Hongchao Zhang:
Generalized Uniformly Optimal Methods for Nonlinear Programming. J. Sci. Comput. 79(3): 1854-1881 (2019) - [j7]Saeed Ghadimi:
Conditional gradient type methods for composite nonlinear and stochastic optimization. Math. Program. 173(1-2): 431-464 (2019) - [i3]Abhishek Roy, Krishnakumar Balasubramanian, Saeed Ghadimi, Prasant Mohapatra:
Multi-Point Bandit Algorithms for Nonstationary Online Nonconvex Optimization. CoRR abs/1907.13616 (2019) - 2018
- [c1]Krishnakumar Balasubramanian, Saeed Ghadimi:
Zeroth-order (Non)-Convex Stochastic Optimization via Conditional Gradient and Gradient Updates. NeurIPS 2018: 3459-3468 - [i2]Krishnakumar Balasubramanian, Saeed Ghadimi:
Zeroth-order (Non)-Convex Stochastic Optimization via Conditional Gradient and Gradient Updates. CoRR abs/1809.06474 (2018) - 2016
- [j6]Saeed Ghadimi, Guanghui Lan, Hongchao Zhang:
Mini-batch stochastic approximation methods for nonconvex stochastic composite optimization. Math. Program. 155(1-2): 267-305 (2016) - [j5]Saeed Ghadimi, Guanghui Lan:
Accelerated gradient methods for nonconvex nonlinear and stochastic programming. Math. Program. 156(1-2): 59-99 (2016) - 2015
- [j4]Reza Zanjirani Farahani, Wai Yuen Szeto, Saeed Ghadimi:
The single facility location problem with time-dependent weights and relocation cost over a continuous time horizon. J. Oper. Res. Soc. 66(2): 265-277 (2015) - 2013
- [j3]Saeed Ghadimi, Guanghui Lan:
Optimal Stochastic Approximation Algorithms for Strongly Convex Stochastic Composite Optimization, II: Shrinking Procedures and Optimal Algorithms. SIAM J. Optim. 23(4): 2061-2089 (2013) - [j2]Saeed Ghadimi, Guanghui Lan:
Stochastic First- and Zeroth-Order Methods for Nonconvex Stochastic Programming. SIAM J. Optim. 23(4): 2341-2368 (2013) - [i1]Saeed Ghadimi, Guanghui Lan:
Stochastic First- and Zeroth-order Methods for Nonconvex Stochastic Programming. CoRR abs/1309.5549 (2013) - 2012
- [j1]Saeed Ghadimi, Guanghui Lan:
Optimal Stochastic Approximation Algorithms for Strongly Convex Stochastic Composite Optimization I: A Generic Algorithmic Framework. SIAM J. Optim. 22(4): 1469-1492 (2012)
Coauthor Index
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