5 citations · 30 across the 20 of their papers we have counts for
14 papers · 1 filter
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…
Multi-granularity Causal Structure Learning
Jiaxuan Liang, Jun Wang, Guoxian Yu +2
Unveil, model, and comprehend the causal mechanisms underpinning natural phenomena stand as fundamental endeavors across myriad scientific disciplines. Meanwhile, new knowledge eme…
GBG++: A Fast and Stable Granular Ball Generation Method for Classification
Qin Xie, Qinghua Zhang, Shuyin Xia +4
Granular ball computing (GBC), as an efficient, robust, and scalable learning method, has become a popular research topic of granular computing. GBC includes two stages: granular b…
Granular-ball computing: an efficient, robust, and interpretable adaptive multi-granularity representation and computation method
Shuyin Xia, Guoyin Wang, Xinbo Gao +2
To overcome the limitations of point-based inputs, overly fine computation and limited adaptability in existing artificial intelligence methods, Guoyin Wang and Shuyin Xia proposed…
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…
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…
GBO:AMulti-Granularity Optimization Algorithm via Granular-ball for Continuous Problems
Shuyin Xia, Xinyu Lin, Guan Wang +4
Optimization problems aim to find the optimal solution, which is becoming increasingly complex and difficult to solve. Traditional evolutionary optimization methods always overlook…
A novel cluster internal evaluation index based on hyper-balls
Jiang Xie, Pengfei Zhao, Shuyin Xia +2
It is crucial to evaluate the quality and determine the optimal number of clusters in cluster analysis. In this paper, the multi-granularity characterization of the data set is car…
Granular-Ball Fuzzy Set and Its Implementation in SVM
Shuyin Xia, Xiaoyu Lian, Guoyin Wang +2
Most existing fuzzy set methods use points as their input, which is the finest granularity from the perspective of granular computing. Consequently, these methods are neither effic…
GBSVM: Granular-ball Support Vector Machine
Shuyin Xia, Xiaoyu Lian, Guoyin Wang +3
GBSVM (Granular-ball Support Vector Machine) is a significant attempt to construct a classifier using the coarse-to-fine granularity of a granular-ball as input, rather than a sing…
GBC: An Efficient and Adaptive Clustering Algorithm Based on Granular-Ball
Shuyin Xia, Jiang Xie, Guoyin Wang
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 usually ineffi…
An Efficient and Accurate Rough Set for Feature Selection, Classification and Knowledge Representation
Shuyin Xia, Xinyu Bai, Guoyin Wang +4
This paper present a strong data mining method based on rough set, which can realize feature selection, classification and knowledge representation at the same time. Rough set has…
An Efficient and Adaptive Granular-ball Generation Method in Classification Problem
Shuyin Xia, Xiaochuan Dai, Guoyin Wang +2
Granular-ball computing is an efficient, robust, and scalable learning method for granular computing. The basis of granular-ball computing is the granular-ball generation method. T…
Ball k-means
Shuyin Xia, Daowan Peng, Deyu Meng +4
This paper presents a novel accelerated exact k-means algorithm called the Ball k-means algorithm, which uses a ball to describe a cluster, focusing on reducing the point-centroid…