Jingrui He

Task-Adversarial Co-Generative Nets

2019

In this paper, we propose Task-Adversarial co-Generative Nets (TAGN) for learning from multiple tasks. It aims to address the two fundamental issues of multi-task learning, i.e., domain shift and limited labeled data, in a principled …

Unlearn What You Have Learned

2018

With the increasing demand for large amount of labeled data, crowdsourcing has been used in many large-scale data mining applications. However, most existing works in crowdsourcing mainly focus on label inference and incentive design. In …

Tackling Oversmoothing of GNNs with Contrastive Learning.

2021 · arXiv (Cornell University)

Graph neural networks (GNNs) integrate the comprehensive relation of graph data and the representation learning capability of neural networks, which is one of the most popular deep learning methods and achieves state-of-the-art performance in many …