Beyond First-Order Methods for $\ell_p$-Structured Non-Monotone Variational Inequalities
Abhijeet Vyas, Brian Bullins

TL;DR
This paper introduces high-order algorithms for $ abla_p$-structured non-monotone variational inequalities, enabling convergence to $ ext{l}_p$-norm stationary points for a broader range of parameters, surpassing previous limitations.
Contribution
It develops high-order methods that achieve convergence to $ ext{l}_p$-norm stationary points for $ ho > 0$, extending prior work limited to $ ho=0$, and generalizes results to monotone operators for $p eq 2$.
Findings
Algorithms converge to $ ext{l}_p$-stationary points for $ ho > 0$
Extended convergence results to monotone operators for $p eq 2$
Techniques adapted to continuous-time settings
Abstract
We propose novel high-order algorithms for a class of -structured non-monotone variational inequalities. In particular, work by Diakonikolas et al. (2021), which introduced the weak Minty variational inequality (weak-MVI) setting, showed how to find an approximate first-order Euclidean stationary point for a strictly positive range of the weak-MVI parameter . However, for the -norm stationary point setting (), their guarantees are limited to , which recovers the standard MVI setting. In this work, we address this gap by presenting a suite of high-order methods that converge to -norm stationary points for a suitable range of , thereby circumventing previous fundamental challenges in settings. We further show convergence for high-order smooth \textit{monotone} operators, generalizing Adil et al. (2022) to the case where $p…
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Taxonomy
TopicsOptimization and Variational Analysis · Stochastic Gradient Optimization Techniques · Contact Mechanics and Variational Inequalities
