On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation

1 code implementation • 22 Jan 2020 • Nicolas Brosse, Carlos Riquelme, Alice Martin, Sylvain Gelly, Éric Moulines

Uncertainty quantification for deep learning is a challenging open problem.

General Classification Representation Learning +1

Learning Natural Language Generation with Truncated Reinforcement Learning

1 code implementation • NAACL 2022 • Alice Martin, Guillaume Quispe, Charles Ollion, Sylvain Le Corff, Florian Strub, Olivier Pietquin

To our knowledge, it is the first approach that successfully learns a language generation policy without pre-training, using only reinforcement learning.

Language Modelling Question Generation +4

The Monte Carlo Transformer: a stochastic self-attention model for sequence prediction

no code implementations • 15 Jul 2020 • Alice Martin, Charles Ollion, Florian Strub, Sylvain Le Corff, Olivier Pietquin

This paper introduces the Sequential Monte Carlo Transformer, an original approach that naturally captures the observations distribution in a transformer architecture.