# Stabilizing Bi-Level Hyperparameter Optimization using Moreau-Yosida Regularization

arXiv: https://arxiv.org/abs/2007.13322 · HTML: https://mlsanity.com/paper/2007.13322/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Jul 2020.

## Built on by (most cited first, 1 of 1)

- [Inexact bilevel stochastic gradient methods for constrained and unconstrained lower-level problems](https://mlsanity.com/paper/2110.00604/) (2021)

## Abstract (arXiv)

This research proposes to use the Moreau-Yosida envelope to stabilize the convergence behavior of bi-level Hyperparameter optimization solvers, and introduces the new algorithm called Moreau-Yosida regularized Hyperparameter Optimization (MY-HPO) algorithm. Theoretical analysis on the correctness of the MY-HPO solution and initial convergence analysis is also provided. Our empirical results show significant improvement in loss values for a fixed computation budget, compared to the state-of-art bi-level HPO solvers.