Selecting task with optimal transport self-supervised learning for few-shot classification

no code implementations • 1 Apr 2022 • Renjie Xu, Xinghao Yang, BaoDi Liu, Kai Zhang, Weifeng Liu

Few-Shot classification aims at solving problems that only a few samples are available in the training process.

Data Augmentation Few-Shot Learning +1

GCT: Graph Co-Training for Semi-Supervised Few-Shot Learning

no code implementations • 15 Mar 2022 • Rui Xu, Lei Xing, Shuai Shao, Lifei Zhao, BaoDi Liu, Weifeng Liu, Yicong Zhou

First, we propose a novel label prediction method, Isolated Graph Learning (IGL).

Classification Few-Shot Learning +1

SSDL: Self-Supervised Dictionary Learning

no code implementations • 3 Dec 2021 • Shuai Shao, Lei Xing, Wei Yu, Rui Xu, Yanjiang Wang, BaoDi Liu

Inspired by the concept of self-supervised learning (e. g., setting the pretext task to generate a universal model for the downstream task), we propose a Self-Supervised Dictionary Learning (SSDL) framework to address this challenge.

Dictionary Learning Human Activity Recognition +1