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Erfan Yazdandoost Hamedani

8 accepted papers

2025

On the Complexity of Finding Stationary Points in Nonconvex Simple Bilevel Optimization

NeurIPS 2025poster

In this paper, we study the problem of solving a simple bilevel optimization problem, where the upper-level objective is minimized over the solution set of the lower-level problem. We focus on the general setting in which both the upper- and lower-level objectives are smooth but potentially nonconve…

Cited by 0SourceScholar
2025

Semi-infinite Nonconvex Constrained Min-Max Optimization

NeurIPS 2025poster

Semi-Infinite Programming (SIP) has emerged as a powerful framework for modeling problems with infinite constraints, however, its theoretical development in the context of nonconvex and large-scale optimization remains limited. In this paper, we investigate a class of nonconvex min-max optimization…

Cited by 0SourceScholar
2024

An Accelerated Gradient Method for Convex Smooth Simple Bilevel Optimization

NeurIPS 2024poster

In this paper, we focus on simple bilevel optimization problems, where we minimize a convex smooth objective function over the optimal solution set of another convex smooth constrained optimization problem. We present a novel bilevel optimization method that locally approximates the solution set of…

Cited by 1SourcePDFScholar
2023

A Conditional Gradient-based Method for Simple Bilevel Optimization with Convex Lower-level Problem

AISTATS 2023poster

In this paper, we study a class of bilevel optimization problems, also known as simple bilevel optimization, where we minimize a smooth objective function over the optimal solution set of another convex constrained optimization problem. Several iterative methods have been developed for tackling this…

2023

Projection-Free Methods for Solving Nonconvex-Concave Saddle Point Problems

NeurIPS 2023poster

In this paper, we investigate a class of constrained saddle point (SP) problems where the objective function is nonconvex-concave and smooth. This class of problems has wide applicability in machine learning, including robust multi-class classification and dictionary learning. Several projection-bas…

Cited by 5SourcePDFScholar
2023

Projection-Free Methods for Stochastic Simple Bilevel Optimization with Convex Lower-level Problem

NeurIPS 2023poster

In this paper, we study a class of stochastic bilevel optimization problems, also known as stochastic simple bilevel optimization, where we minimize a smooth stochastic objective function over the optimal solution set of another stochastic convex optimization problem. We introduce novel stochastic b…

Cited by 10SourcePDFScholar
2023

Randomized Primal-Dual Methods with Adaptive Step Sizes

AISTATS 2023poster

In this paper we propose a class of randomized primal-dual methods incorporating line search to contend with large-scale saddle point (SP) problems defined by a convex-concave function $\mathcal L(\mathbf{x},y) = \sum_{i=1}^M f_i(x_i)+\Phi(\mathbf{x},y)-h(y)$. We analyze the convergence rate of the…

Cited by 4SourcePDFScholar
2016

A primal-dual method for conic constrained distributed optimization problems

NeurIPS 2016poster

We consider cooperative multi-agent consensus optimization problems over an undirected network of agents, where only those agents connected by an edge can directly communicate. The objective is to minimize the sum of agent-specific composite convex functions over agent-specific private conic constra…

Cited by 51SourcePDFScholar