AUTOKD: Automatic Knowledge Distillation Into A Student Architecture Family

no code implementations • 5 Nov 2021 • Roy Henha Eyono, Fabio Maria Carlucci, Pedro M Esperança, Binxin Ru, Phillip Torr

State-of-the-art results in deep learning have been improving steadily, in good part due to the use of larger models.

Bayesian Optimization Knowledge Distillation +1

Don't be picky, all students in the right family can learn from good teachers

no code implementations • 1 Jan 2021 • Roy Henha Eyono, Fabio Maria Carlucci, Pedro M Esperança, Binxin Ru, Philip Torr

State-of-the-art results in deep learning have been improving steadily, in good part due to the use of larger models.

Bayesian Optimization Knowledge Distillation +1

MANAS: Multi-Agent Neural Architecture Search

no code implementations • 3 Sep 2019 • Vasco Lopes, Fabio Maria Carlucci, Pedro M Esperança, Marco Singh, Victor Gabillon, Antoine Yang, Hang Xu, Zewei Chen, Jun Wang

The Neural Architecture Search (NAS) problem is typically formulated as a graph search problem where the goal is to learn the optimal operations over edges in order to maximise a graph-level global objective.

Neural Architecture Search