NEURIPS 2025 "minimax optimization" Papers

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Adaptive Algorithms with Sharp Convergence Rates for Stochastic Hierarchical Optimization

Xiaochuan Gong, Jie Hao, Mingrui Liu

NEURIPS 2025posterarXiv:2509.15399
1
citations

FraPPE: Fast and Efficient Preference-Based Pure Exploration

Udvas Das, Apurv Shukla, Debabrota Basu

NEURIPS 2025posterarXiv:2508.16487

Online Optimization for Offline Safe Reinforcement Learning

Yassine Chemingui, Aryan Deshwal, Alan Fern et al.

NEURIPS 2025posterarXiv:2510.22027

On the Convergence of Stochastic Smoothed Multi-Level Compositional Gradient Descent Ascent

Xinwen Zhang, Hongchang Gao

NEURIPS 2025poster

Quantum Speedups for Minimax Optimization and Beyond

Chengchang Liu, Zongqi Wan, Institute of Computing Jialin Zhang et al.

NEURIPS 2025poster

Robust Minimax Boosting with Performance Guarantees

Santiago Mazuelas, Veronica Alvarez

NEURIPS 2025posterarXiv:2510.13445