5 citations · 23 across the 23 of their papers we have counts for
23 papers
Granular-Ball Quantum Clustering for Resource-Efficient and Robust Learning
Suzhen Yuan, Qilin Xie, Lifeng Shen +3
Quantum clustering aims to exploit quantum feature representations to uncover complex data structures beyond conventional Euclidean geometry. Yet this sample-level kernel construct…
Adaptive Nearest Neighbors Classifier via Granular Ball Computing
Xiaoyu Lian, Shuyin Xia, Hongxuan He +3
The -Nearest Neighbor~(KNN) algorithm is widely used across various tasks. The selection of the value is a key issue because it significantly impacts performance. In this pa…
Efficient and Scalable Granular-ball Graph Coarsening Method for Large-scale Graph Node Classification
Guan Wang, Shuyin Xia, Lei Qian +4
Graph Convolutional Network (GCN) is a model that can effectively handle graph data tasks and has been successfully applied. However, for large-scale graph datasets, GCN still face…
Square Superpixel Generation and Representation Learning via Granular Ball Computing
Shuyin Xia, Meng Yang, Dawei Dai +6
Superpixels provide a compact region-based representation that preserves object boundaries and local structures, and have therefore been widely used in a variety of vision tasks to…
Implicit Non-Causal Factors are Out via Dataset Splitting for Domain Generalization Object Detection
Zhilong Zhang, Lei Zhang, Qing He +3
Open world object detection faces a significant challenge in domain-invariant representation, i.e., implicit non-causal factors. Most domain generalization (DG) methods based on do…
GBSK: Skeleton Clustering via Granular-ball Computing and Multi-Sampling for Large-Scale Data
Yewang Chen, Junfeng Li, Shuyin Xia +6
To effectively handle clustering task for large-scale datasets, we propose a novel scalable skeleton clustering algorithm, namely GBSK, which leverages the granular-ball technique…
Granular-Ball-Induced Multiple Kernel K-Means
Shuyin Xia, Yifan Wang, Lifeng Shen +1
Most existing multi-kernel clustering algorithms, such as multi-kernel K-means, often struggle with computational efficiency and robustness when faced with complex data distributio…
GBFRS: Robust Fuzzy Rough Sets via Granular-ball Computing
Shuyin Xia, Xiaoyu Lian, Binbin Sang +2
Fuzzy rough set theory is effective for processing datasets with complex attributes, supported by a solid mathematical foundation and closely linked to kernel methods in machine le…
A New Perspective on Privacy Protection in Federated Learning with Granular-Ball Computing
Guannan Lai, Yihui Feng, Xin Yang +5
Federated Learning (FL) facilitates collaborative model training while prioritizing privacy by avoiding direct data sharing. However, most existing articles attempt to address chal…
Graph Coarsening via Supervised Granular-Ball for Scalable Graph Neural Network Training
Shuyin Xia, Xinjun Ma, Zhiyuan Liu +3
Graph Neural Networks (GNNs) have demonstrated significant achievements in processing graph data, yet scalability remains a substantial challenge. To address this, numerous graph c…
Multi-Granularity Open Intent Classification via Adaptive Granular-Ball Decision Boundary
Yanhua Li, Xiaocao Ouyang, Chaofan Pan +6
Open intent classification is critical for the development of dialogue systems, aiming to accurately classify known intents into their corresponding classes while identifying unkno…
GBCT: An Efficient and Adaptive Granular-Ball Clustering Algorithm for Complex Data
Shuyin Xia, Bolun Shi, Yifan Wang +3
Traditional clustering algorithms often focus on the most fine-grained information and achieve clustering by calculating the distance between each pair of data points or implementi…
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…
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…
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…
Graph-based Representation for Image based on Granular-ball
Xia Shuyin, Dai Dawei, Yang Long +4
Current image processing methods usually operate on the finest-granularity unit; that is, the pixel, which leads to challenges in terms of efficiency, robustness, and understandabi…
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…
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…