2 citations · 3 across the 4 of their papers we have counts for
4 papers
DM: Dataset Distillation via Disentangled Diffusion Model
Duo Su, Junjie Hou, Weizhi Gao +2
Dataset distillation offers a lightweight synthetic dataset for fast network training with promising test accuracy. To imitate the performance of the original dataset, most approac…
Message-passing selection: Towards interpretable GNNs for graph classification
Wenda Li, Kaixuan Chen, Shunyu Liu +5
In this paper, we strive to develop an interpretable GNNs' inference paradigm, termed MSInterpreter, which can serve as a plug-and-play scheme readily applicable to various GNNs' b…
PIGMIL: Positive Instance Detection via Graph Updating for Multiple Instance Learning
Dongkuan Xu, Jia Wu, Wei Zhang +1
Positive instance detection, especially for these in positive bags (true positive instances, TPIs), plays a key role for multiple instance learning (MIL) arising from a specific cl…
Multi-view metric learning for multi-instance image classification
Dewei Li, Yingjie Tian
It is critical and meaningful to make image classification since it can help human in image retrieval and recognition, object detection, etc. In this paper, three-sides efforts are…