1 citations · 1 across the 14 of their papers we have counts for
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Improving Online-to-Nonconvex Conversion for Smooth Optimization via Double Optimism
Francisco Patitucci, Ruichen Jiang, Aryan Mokhtari
A recent breakthrough in nonconvex optimization is the online-to-nonconvex conversion framework of [Cutkosky et al., 2023], which reformulates the task of finding an -…
On the Complexity of Finding Stationary Points in Nonconvex Simple Bilevel Optimization
Jincheng Cao, Ruichen Jiang, Erfan Yazdandoost Hamedani +1
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.…
Affine-Invariant Global Non-Asymptotic Convergence Analysis of BFGS under Self-Concordance
Qiujiang Jin, Aryan Mokhtari
In this paper, we establish global non-asymptotic convergence guarantees for the BFGS quasi-Newton method without requiring strong convexity or the Lipschitz continuity of the grad…
Online Learning-guided Learning Rate Adaptation via Gradient Alignment
Ruichen Jiang, Ali Kavis, Aryan Mokhtari
The performance of an optimizer on large-scale deep learning models depends critically on fine-tuning the learning rate, often requiring an extensive grid search over base learning…