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20232026
most citedFully First-Order Methods for Decentralized Bilevel Optimization

1 citations · 1 across the 6 of their papers we have counts for

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7 papers

math.OC2026

Peppy: An AI-Assisted Workflow for Tight Convergence Analysis of Optimization Algorithms

Jaewook J. Suh, TaeHo Yoon, Edward Duc Hien Nguyen +2

This paper presents Peppy, an AI-assisted workflow for discovering tight, analytic convergence proofs for first-order optimization algorithms. Generic approaches to using LLMs to c…

math.OC2026

Toward a Systematic Understanding and Interactive Search of Lyapunov-Style Proofs in Optimization

TaeHo Yoon, Jaewook J. Suh, Edward Duc Hien Nguyen +2

Lyapunov-style convergence proofs, which establish a nonincreasing sequence to provide a quantitative convergence rate for an algorithm, are popular and often considered desirable…

math.OC2025

On Relatively Smooth Optimization over Riemannian Manifolds

Chang He, Jiaxiang Li, Bo Jiang +2

We study optimization over Riemannian embedded submanifolds, where the objective function is relatively smooth in the ambient Euclidean space. Such problems have broad applications…

math.OC2024★ 1 cited

Fully First-Order Methods for Decentralized Bilevel Optimization

Xiaoyu Wang, Xuxing Chen, Shiqian Ma +1

This paper focuses on decentralized stochastic bilevel optimization (DSBO) where agents only communicate with their neighbors. We propose Decentralized Stochastic Gradient Descent…

math.OC2024

Problem-Parameter-Free Decentralized Nonconvex Stochastic Optimization

Jiaxiang Li, Xuxing Chen, Shiqian Ma +1

Existing decentralized algorithms usually require knowledge of problem parameters for updating local iterates. For example, the hyperparameters (such as learning rate) usually requ…

math.OC2024

Riemannian Bilevel Optimization

Jiaxiang Li, Shiqian Ma

In this work, we consider the bilevel optimization problem on Riemannian manifolds. We inspect the calculation of the hypergradient of such problems on general manifolds and thus e…

math.OC2023

Zeroth-order Riemannian Averaging Stochastic Approximation Algorithms

Jiaxiang Li, Krishnakumar Balasubramanian, Shiqian Ma

We present Zeroth-order Riemannian Averaging Stochastic Approximation (\texttt{Zo-RASA}) algorithms for stochastic optimization on Riemannian manifolds. We show that \texttt{Zo-RAS…