1 citations · 2 across the 7 of their papers we have counts for
7 papers
Faithful Density-Peaks Clustering via Matrix Computations on MPI Parallelization System
Ji Xu, Tianlong Xiao, Jinye Yang +1
Density peaks clustering (DP) has the ability of detecting clusters of arbitrary shape and clustering non-Euclidean space data, but its quadratic complexity in both computing and s…
Long-Tailed Classification Based on Coarse-Grained Leading Forest and Multi-Center Loss
Jinye Yang, Ji Xu, Di Wu +3
Long-tailed (LT) classification is an unavoidable and challenging problem in the real world. Most existing long-tailed classification methods focus only on solving the class-wise i…
Determinate Node Selection for Semi-supervised Classification Oriented Graph Convolutional Networks
Yao Xiao, Ji Xu, Jing Yang +1
Graph Convolutional Networks (GCNs) have been proved successful in the field of semi-supervised node classification by extracting structural information from graph data. However, t…
Semi-supervised Learning with Deterministic Labeling and Large Margin Projection
Ji Xu, Gang Ren, Yao Xiao +2
The centrality and diversity of the labeled data are very influential to the performance of semi-supervised learning (SSL), but most SSL models select the labeled data randomly. Th…
The Multi-granularity in Graph Revealed by a Generalized Leading Tree
Shun Fu, Ji Xu
There are hierarchical characteristics in the network and how to effectively reveal the hierarchical characteristics in the network is a problem in the research of network structur…
Non-iterative Label Propagation in Optimal Leading Forest
Ji Xu, Guoyin Wang
Graph based semi-supervised learning (GSSL) has intuitive representation and can be improved by exploiting the matrix calculation. However, it has to perform iterative optimization…
Leading Tree in DPCLUS and Its Impact on Building Hierarchies
Ji Xu, Guoyin Wang
This paper reveals the tree structure as an intermediate result of clustering by fast search and find of density peaks (DPCLUS), and explores the power of using this tree to perfor…