Saeed Ghadimi

Orcid: 0000-0002-3191-5153

According to our database1, Saeed Ghadimi authored at least 29 papers between 2012 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Stochastic search for a parametric cost function approximation: Energy storage with rolling forecasts.
Eur. J. Oper. Res., January, 2024

An Adversarially Robust Formulation of Linear Regression With Missing Data.
IEEE Trans. Signal Process., 2024

Fully Zeroth-Order Bilevel Programming via Gaussian Smoothing.
CoRR, 2024

2023
Stochastic Nested Compositional Bi-level Optimization for Robust Feature Learning.
CoRR, 2023

Learn What NOT to Learn: Towards Generative Safety in Chatbots.
CoRR, 2023

A one-sample decentralized proximal algorithm for non-convex stochastic composite optimization.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

2022
Stochastic Multilevel Composition Optimization Algorithms with Level-Independent Convergence Rates.
SIAM J. Optim., 2022

Improved complexities for stochastic conditional gradient methods under interpolation-like conditions.
Oper. Res. Lett., 2022

Stochastic Zeroth-Order Optimization under Nonstationarity and Nonconvexity.
J. Mach. Learn. Res., 2022

Zeroth-Order Nonconvex Stochastic Optimization: Handling Constraints, High Dimensionality, and Saddle Points.
Found. Comput. Math., 2022

Projection-free Constrained Stochastic Nonconvex Optimization with State-dependent Markov Data.
CoRR, 2022

RIGID: Robust Linear Regression with Missing Data.
CoRR, 2022

The Parametric Cost Function Approximation: A new approach for multistage stochastic programming.
CoRR, 2022

A Projection-free Algorithm for Constrained Stochastic Multi-level Composition Optimization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Constrained Stochastic Nonconvex Optimization with State-dependent Markov Data.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2020
A Single Timescale Stochastic Approximation Method for Nested Stochastic Optimization.
SIAM J. Optim., 2020

Escaping Saddle-Points Faster under Interpolation-like Conditions.
CoRR, 2020

Stochastic Multi-level Composition Optimization Algorithms with Level-Independent Convergence Rates.
CoRR, 2020

Escaping Saddle-Point Faster under Interpolation-like Conditions.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
Conditional gradient type methods for composite nonlinear and stochastic optimization.
Math. Program., 2019

Generalized Uniformly Optimal Methods for Nonlinear Programming.
J. Sci. Comput., 2019

Multi-Point Bandit Algorithms for Nonstationary Online Nonconvex Optimization.
CoRR, 2019

2018
Zeroth-order (Non)-Convex Stochastic Optimization via Conditional Gradient and Gradient Updates.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2016
Mini-batch stochastic approximation methods for nonconvex stochastic composite optimization.
Math. Program., 2016

Accelerated gradient methods for nonconvex nonlinear and stochastic programming.
Math. Program., 2016

2015
The single facility location problem with time-dependent weights and relocation cost over a continuous time horizon.
J. Oper. Res. Soc., 2015

2013
Stochastic First- and Zeroth-Order Methods for Nonconvex Stochastic Programming.
SIAM J. Optim., 2013

Optimal Stochastic Approximation Algorithms for Strongly Convex Stochastic Composite Optimization, II: Shrinking Procedures and Optimal Algorithms.
SIAM J. Optim., 2013

2012
Optimal Stochastic Approximation Algorithms for Strongly Convex Stochastic Composite Optimization I: A Generic Algorithmic Framework.
SIAM J. Optim., 2012


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