Qiujiang Jin

12 papers A* 5Journal 7
YearRankTypeTitle / Venue / Authors
2025 J jnl
Affine-Invariant Global Non-Asymptotic Convergence Analysis of BFGS under Self-Concordance.
CoRR
Qiujiang Jin, Aryan Mokhtari
2024 A* conf
Adaptive and Optimal Second-order Optimistic Methods for Minimax Optimization.
NeurIPS
Ruichen Jiang, Ali Kavis, Qiujiang Jin, Sujay Sanghavi, Aryan Mokhtari
2024 J jnl
Adaptive and Optimal Second-order Optimistic Methods for Minimax Optimization.
CoRR
Ruichen Jiang, Ali Kavis, Qiujiang Jin, Sujay Sanghavi, Aryan Mokhtari
2024 A* conf
Non-asymptotic Global Convergence Analysis of BFGS with the Armijo-Wolfe Line Search.
NeurIPS
Qiujiang Jin, Ruichen Jiang, Aryan Mokhtari
2024 J jnl
Statistical and Computational Complexities of BFGS Quasi-Newton Method for Generalized Linear Models.
Trans. Mach. Learn. Res.
Qiujiang Jin, Tongzheng Ren, Nhat Ho, Aryan Mokhtari
2023 J jnl
Non-asymptotic superlinear convergence of standard quasi-Newton methods.
Math. Program.
Qiujiang Jin, Aryan Mokhtari
2023 A* conf
Online Learning Guided Curvature Approximation: A Quasi-Newton Method with Global Non-Asymptotic Superlinear Convergence.
COLT
Ruichen Jiang, Qiujiang Jin, Aryan Mokhtari
2023 J jnl
Online Learning Guided Curvature Approximation: A Quasi-Newton Method with Global Non-Asymptotic Superlinear Convergence.
CoRR
Ruichen Jiang, Qiujiang Jin, Aryan Mokhtari
2022 A* conf
Sharpened Quasi-Newton Methods: Faster Superlinear Rate and Larger Local Convergence Neighborhood.
ICML
Qiujiang Jin, Alec Koppel, Ketan Rajawat, Aryan Mokhtari
2021 A* conf
Exploiting Local Convergence of Quasi-Newton Methods Globally: Adaptive Sample Size Approach.
NeurIPS
Qiujiang Jin, Aryan Mokhtari
2021 J jnl
Exploiting Local Convergence of Quasi-Newton Methods Globally: Adaptive Sample Size Approach.
CoRR
Qiujiang Jin, Aryan Mokhtari
2020 J jnl
Non-asymptotic Superlinear Convergence of Standard Quasi-Newton Methods.
CoRR
Qiujiang Jin, Aryan Mokhtari