Global Convergence and Variance Reduction for a Class of Nonconvex-Nonconcave Minimax Problems. - Junchi Yang; Negar Kiyavash; Niao He (NeurIPS, 2020)

A Catalyst Framework for Minimax Optimization. - Junchi Yang; Siqi Zhang; Negar Kiyavash; Niao He (NeurIPS, 2020)

Global Convergence and Variance-Reduced Optimization for a Class of Nonconvex-Nonconcave Minimax Problems. - Junchi Yang; Negar Kiyavash; Niao He (CoRR, 2020)

The complexity of nonconvex-strongly-concave minimax optimization. - Siqi Zhang; Junchi Yang; Cristóbal Guzmán; Negar Kiyavash; Niao He (UAI, 2021)

Faster Single-loop Algorithms for Minimax Optimization without Strong Concavity. - Junchi Yang; Antonio Orvieto; Aurélien Lucchi; Niao He (AISTATS, 2022)

Nest Your Adaptive Algorithm for Parameter-Agnostic Nonconvex Minimax Optimization. - Junchi Yang; Xiang Li; Niao He (NeurIPS, 2022)

TiAda: A Time-scale Adaptive Algorithm for Nonconvex Minimax Optimization. - Xiang Li; Junchi Yang; Niao He (ICLR, 2023)

Two Sides of One Coin: the Limits of Untuned SGD and the Power of Adaptive Methods. - Junchi Yang; Xiang Li; Ilyas Fatkhullin; Niao He (NeurIPS, 2023)

Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization. - Liang Zhang; Junchi Yang; Amin Karbasi; Niao He (NeurIPS, 2023)

Towards Near-Optimal and Adaptive Algorithms in Minimax Optimization. - Junchi Yang (2023)

Parameter-Agnostic Optimization under Relaxed Smoothness. - Florian Hübler; Junchi Yang; Xiang Li; Niao He (AISTATS, 2024)

Accelerating Distributed Optimization: A Primal-Dual Perspective on Local Steps. - Junchi Yang; Murat Yildirim; Qiu Feng (CoRR, 2024)

Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives. - Yajiao Liu; Congliang Chen; Junchi Yang; Ruoyu Sun 001 (CoRR, 2025)