no code implementations • ACL (MetaNLP) 2021 • Cyprien de Lichy, Hadrien Glaude, William Campbell
Meta-learning has recently been proposed to learn models and algorithms that can generalize from a handful of examples.
no code implementations • 28 Jan 2021 • Manoj Kumar, Varun Kumar, Hadrien Glaude, Cyprien delichy, Aman Alok, Rahul Gupta
We make use of a conditional generator for data augmentation that is trained directly using the meta-learning objective and simultaneously with prototypical networks, hence ensuring that data augmentation is customized to the task.
no code implementations • WS 2019 • Varun Kumar, Hadrien Glaude, Cyprien de Lichy, William Campbell
In particular, we show that (a) upsampling in latent space is a competitive baseline for feature space augmentation (b) adding the difference between two examples to a new example is a simple yet effective data augmentation method.