27 citations · 40 across the 3 of their papers we have counts for
3 papers · 1 filter
Self-Supervised Prototypical Transfer Learning for Few-Shot Classification
Carlos Medina, Arnout Devos, Matthias Grossglauser
Most approaches in few-shot learning rely on costly annotated data related to the goal task domain during (pre-)training. Recently, unsupervised meta-learning methods have exchange…
Learning Hawkes Processes from a Handful of Events
Farnood Salehi, William Trouleau, Matthias Grossglauser +1
Learning the causal-interaction network of multivariate Hawkes processes is a useful task in many applications. Maximum-likelihood estimation is the most common approach to solve t…
Regression Networks for Meta-Learning Few-Shot Classification
Arnout Devos, Matthias Grossglauser
We propose regression networks for the problem of few-shot classification, where a classifier must generalize to new classes not seen in the training set, given only a small number…