most citedOpen Continual Feature Selection via Granular-Ball Knowledge Transfer

1 citations · 5 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2024

Granular-ball Representation Learning for Deep CNN on Learning with Label Noise

Dawei Dai, Hao Zhu, Shuyin Xia +1

In actual scenarios, whether manually or automatically annotated, label noise is inevitably generated in the training data, which can affect the effectiveness of deep CNN models. T…

cs.AI20241 cited

PA-LLaVA: A Large Language-Vision Assistant for Human Pathology Image Understanding

Dawei Dai, Yuanhui Zhang, Long Xu +4

The previous advancements in pathology image understanding primarily involved developing models tailored to specific tasks. Recent studies has demonstrated that the large vision-la…

cs.LG2024

A robust three-way classifier with shadowed granular-balls based on justifiable granularity

Jie Yang, Lingyun Xiaodiao, Guoyin Wang +4

The granular-ball (GB)-based classifier introduced by Xia, exhibits adaptability in creating coarse-grained information granules for input, thereby enhancing its generality and fle…

cs.LG20241 cited

Open Continual Feature Selection via Granular-Ball Knowledge Transfer

Xuemei Cao, Xin Yang, Shuyin Xia +2

This paper presents a novel framework for continual feature selection (CFS) in data preprocessing, particularly in the context of an open and dynamic environment where unknown clas…

cs.LG20231 cited

GBMST: An Efficient Minimum Spanning Tree Clustering Based on Granular-Ball Computing

Jiang Xie, Shuyin Xia, Guoyin Wang +1

Most of the existing clustering methods are based on a single granularity of information, such as the distance and density of each data. This most fine-grained based approach is us…

cs.LG20231 cited

Research on Efficient Fuzzy Clustering Method Based on Local Fuzzy Granular balls

Jiang Xie, Qiao Deng, Shuyin Xia +3

In recent years, the problem of fuzzy clustering has been widely concerned. The membership iteration of existing methods is mostly considered globally, which has considerable probl…