5 citations · 23 across the 23 of their papers we have counts for
5 papers · 1 filter
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…