1 citations · 1 across the 9 of their papers we have counts for
9 papers
DK-GBMKKM: Dynamic Kernel-Space Granular-Ball Multiple Kernel -Means Clustering
Xiaoyu Lian, Yuchao Zhang, Shuyin Xia +2
Multiple kernel -means integrates complementary nonlinear similarities by learning a combination of base kernels. Its pointwise optimization, however, is sensitive to noisy and…
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…
Multi-Granularity Position Embedding of Graphs via Granular-Ball for Link Prediction
Sen Zhao, Cheng Liu, Shuyin Xia +4
Link prediction aims to identify potential or future connections within a given graph structure. Position information is essential for link prediction, as it distinguishes homogene…
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…
GBGC: Efficient and Adaptive Graph Coarsening via Granular-ball Computing
Shuyin Xia, Guan Wang, Gaojie Xu +2
The objective of graph coarsening is to generate smaller, more manageable graphs while preserving key information of the original graph. Previous work were mainly based on the pers…
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…
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…