77 citations · 150 across the 10 of their papers we have counts for
3 papers · 1 filter
Multi-objective Asynchronous Successive Halving
Robin Schmucker, Michele Donini, Muhammad Bilal Zafar +2
Hyperparameter optimization (HPO) is increasingly used to automatically tune the predictive performance (e.g., accuracy) of machine learning models. However, in a plethora of real-…
A multi-objective perspective on jointly tuning hardware and hyperparameters
David Salinas, Valerio Perrone, Olivier Cruchant +1
In addition to the best model architecture and hyperparameters, a full AutoML solution requires selecting appropriate hardware automatically. This can be framed as a multi-objectiv…
A resource-efficient method for repeated HPO and NAS problems
Giovanni Zappella, David Salinas, Cédric Archambeau
In this work we consider the problem of repeated hyperparameter and neural architecture search (HNAS). We propose an extension of Successive Halving that is able to leverage inform…