3 papers
cs.LG2021
Scaling Laws for the Few-Shot Adaptation of Pre-trained Image Classifiers
Gabriele Prato, Simon Guiroy, Ethan Caballero +2
Empirical science of neural scaling laws is a rapidly growing area of significant importance to the future of machine learning, particularly in the light of recent breakthroughs ac…
cs.CL2019
Fully Quantized Transformer for Machine Translation
Gabriele Prato, Ella Charlaix, Mehdi Rezagholizadeh
State-of-the-art neural machine translation methods employ massive amounts of parameters. Drastically reducing computational costs of such methods without affecting performance has…
cs.CL2019
Towards Lossless Encoding of Sentences
Gabriele Prato, Mathieu Duchesneau, Sarath Chandar +1
A lot of work has been done in the field of image compression via machine learning, but not much attention has been given to the compression of natural language. Compressing text i…