no code implementations • 17 Aug 2021 • Saul Calderon-Ramirez, Shengxiang Yang, David Elizondo, Armaghan Moemeni
This results in a distribution mismatch between the unlabelled and labelled datasets.
no code implementations • 19 Aug 2020 • Saul Calderon-Ramirez, Shengxiang-Yang, Armaghan Moemeni, David Elizondo, Simon Colreavy-Donnelly, Luis Fernando Chavarria-Estrada, Miguel A. Molina-Cabello
In this work we evaluate the performance of the semi-supervised deep learning architecture known as MixMatch using a very limited number of labelled observations and highly imbalanced labelled dataset.
1 code implementation • 14 Jun 2020 • Saul Calderon-Ramirez, Luis Oala, Jordina Torrents-Barrena, Shengxiang Yang, Armaghan Moemeni, Wojciech Samek, Miguel A. Molina-Cabello
In this work, we propose MixMOOD - a systematic approach to mitigate effect of class distribution mismatch in semi-supervised deep learning (SSDL) with MixMatch.