81 citations · 154 across the 5 of their papers we have counts for
3 papers · 1 filter
ForkMerge: Mitigating Negative Transfer in Auxiliary-Task Learning
Junguang Jiang, Baixu Chen, Junwei Pan +4
Auxiliary-Task Learning (ATL) aims to improve the performance of the target task by leveraging the knowledge obtained from related tasks. Occasionally, learning multiple tasks simu…
Debiased Self-Training for Semi-Supervised Learning
Baixu Chen, Junguang Jiang, Ximei Wang +3
Deep neural networks achieve remarkable performances on a wide range of tasks with the aid of large-scale labeled datasets. Yet these datasets are time-consuming and labor-exhausti…
Transferability in Deep Learning: A Survey
Junguang Jiang, Yang Shu, Jianmin Wang +1
The success of deep learning algorithms generally depends on large-scale data, while humans appear to have inherent ability of knowledge transfer, by recognizing and applying relev…