8 citations · 12 across the 2 of their papers we have counts for
2 papers
cs.LG2017★ 8 cited
Neural Networks Regularization Through Class-wise Invariant Representation Learning
Soufiane Belharbi, Clément Chatelain, Romain Hérault +1
Training deep neural networks is known to require a large number of training samples. However, in many applications only few training samples are available. In this work, we tackle…
cs.DS2015★ 4 cited
Graph edit distance : a new binary linear programming formulation
Julien Lerouge, Zeina Abu-Aisheh, Romain Raveaux +2
Graph edit distance (GED) is a powerful and flexible graph matching paradigm that can be used to address different tasks in structural pattern recognition, machine learning, and da…