1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Asymmetric Learning for Spectral Graph Neural Networks
Fangbing Liu, Qing Wang
Optimizing spectral graph neural networks (GNNs) remains a critical challenge in the field, yet the underlying processes are not well understood. In this paper, we investigate the…
cs.CV2021
Episode Adaptive Embedding Networks for Few-shot Learning
Fangbing Liu, Qing Wang
Few-shot learning aims to learn a classifier using a few labelled instances for each class. Metric-learning approaches for few-shot learning embed instances into a high-dimensional…
cs.LG2019★ 1 cited
Learning to Sample: an Active Learning Framework
Jingyu Shao, Qing Wang, Fangbing Liu
Meta-learning algorithms for active learning are emerging as a promising paradigm for learning the ``best'' active learning strategy. However, current learning-based active learnin…