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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…

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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…

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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 1Source ↗PDF ↗Scholar ↗
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 5Source ↗PDF ↗Scholar ↗
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 10Source ↗PDF ↗Scholar ↗
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 4Source ↗PDF ↗Scholar ↗
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 51Source ↗PDF ↗Scholar ↗