5 citations · 16 across the 8 of their papers we have counts for
8 papers
Multi-granularity Adaptive Hypergraph Representation Learning via Granular-ball
Sen Zhao, Yifan Guan, Jinyuan Ni +6
Hypergraph representation learning aims to capture high-order information in graphs by constructing hyperedges that simultaneously connect multiple nodes. These hyperedges adapt to…
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…
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…
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…
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…
Boosting the Discriminant Power of Naive Bayes
Shihe Wang, Jianfeng Ren, Xiaoyu Lian +2
Naive Bayes has been widely used in many applications because of its simplicity and ability in handling both numerical data and categorical data. However, lack of modeling of corre…