285 citations · 333 across the 13 of their papers we have counts for
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cs.LG2023★ 1 cited
Improvable Gap Balancing for Multi-Task Learning
Yanqi Dai, Nanyi Fei, Zhiwu Lu
In multi-task learning (MTL), gradient balancing has recently attracted more research interest than loss balancing since it often leads to better performance. However, loss balanci…
cs.LG2022
A Roadmap for Big Model
Sha Yuan, Hanyu Zhao, Shuai Zhao +97
With the rapid development of deep learning, training Big Models (BMs) for multiple downstream tasks becomes a popular paradigm. Researchers have achieved various outcomes in the c…
cs.LG2020★ 12 cited
Meta-Learning across Meta-Tasks for Few-Shot Learning
Nanyi Fei, Zhiwu Lu, Yizhao Gao +3
Existing meta-learning based few-shot learning (FSL) methods typically adopt an episodic training strategy whereby each episode contains a meta-task. Across episodes, these tasks a…