
layout: blog_detail
title: "Efficient Multi-Objective Neural Architecture Search with Ax"
author: David Eriksson, Max Balandat
featured-img: "/assets/images/MOO-NAS-blog-img2-pareto_frontier_plot.png"

tl;dr
Multi-Objective Optimization in Ax enables efficient exploration of tradeoffs (e.g. between model performance and model size or latency) in Neural Architecture Search. This method has been successfully applied at Meta for a variety of products such as On-Device AI. In this post, we provide an end-to-end tutorial that allows you to try it out yourself.
Introduction