Saeed Ghadimi

Warren B. Powell

Eur. J. Oper. Res., January, 2024

2023

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

[BibT_eX]

[DOI]

Xuxing Chen

CoRR, 2023

Learn What NOT to Learn: Towards Generative Safety in Chatbots.

[BibT_eX]

[DOI]

CoRR, 2023

A one-sample decentralized proximal algorithm for non-convex stochastic composite optimization.

[BibT_eX]

[DOI]

Tesi Xiao

Xuxing Chen

Proceedings of the Uncertainty in Artificial Intelligence, 2023

2022

Stochastic Multilevel Composition Optimization Algorithms with Level-Independent Convergence Rates.

[BibT_eX]

[DOI]

Anthony Nguyen

SIAM J. Optim., 2022

Improved complexities for stochastic conditional gradient methods under interpolation-like conditions.

[BibT_eX]

[DOI]

Tesi Xiao

Oper. Res. Lett., 2022

Stochastic Zeroth-Order Optimization under Nonstationarity and Nonconvexity.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2022

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

[BibT_eX]

[DOI]

Found. Comput. Math., 2022

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

[BibT_eX]

[DOI]

CoRR, 2022

RIGID: Robust Linear Regression with Missing Data.

[BibT_eX]

[DOI]

Alireza Aghasi

MohammadJavad Feizollahi

CoRR, 2022

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

[BibT_eX]

[DOI]

Warren B. Powell

CoRR, 2022

A Projection-free Algorithm for Constrained Stochastic Multi-level Composition Optimization.

[BibT_eX]

[DOI]

Tesi Xiao

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Andrzej Ruszczynski

Mengdi Wang

SIAM J. Optim., 2020

Escaping Saddle-Points Faster under Interpolation-like Conditions.

[BibT_eX]

[DOI]

CoRR, 2020

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

[BibT_eX]

[DOI]

Anthony Nguyen

CoRR, 2020

Escaping Saddle-Point Faster under Interpolation-like Conditions.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Math. Program., 2019

Generalized Uniformly Optimal Methods for Nonlinear Programming.

[BibT_eX]

[DOI]

Hongchao Zhang

J. Sci. Comput., 2019

Multi-Point Bandit Algorithms for Nonstationary Online Nonconvex Optimization.

[BibT_eX]

[DOI]

CoRR, 2019

2018

Zeroth-order (Non)-Convex Stochastic Optimization via Conditional Gradient and Gradient Updates.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Hongchao Zhang

Math. Program., 2016

Accelerated gradient methods for nonconvex nonlinear and stochastic programming.

[BibT_eX]

[DOI]

Math. Program., 2016

2015

The single facility location problem with time-dependent weights and relocation cost over a continuous time horizon.

[BibT_eX]

[DOI]

Reza Zanjirani Farahani

Wai Yuen Szeto

J. Oper. Res. Soc., 2015

2013

Stochastic First- and Zeroth-Order Methods for Nonconvex Stochastic Programming.

[BibT_eX]

[DOI]

SIAM J. Optim., 2013

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

[BibT_eX]

[DOI]

SIAM J. Optim., 2013

2012

Optimal Stochastic Approximation Algorithms for Strongly Convex Stochastic Composite Optimization I: A Generic Algorithmic Framework.

[BibT_eX]

[DOI]