activity
20192022
most citedAttention-driven Graph Clustering Network

3 citations · 7 across the 6 of their papers we have counts for

collaborators

9 papers

cs.LG20221 cited

A Parameter-free Nonconvex Low-rank Tensor Completion Model for Spatiotemporal Traffic Data Recovery

Yang He, Yuheng Jia, Liyang Hu +3

Traffic data chronically suffer from missing and corruption, leading to accuracy and utility reduction in subsequent Intelligent Transportation System (ITS) applications. Noticing…

cs.CV20213 cited

Attention-driven Graph Clustering Network

Zhihao Peng, Hui Liu, Yuheng Jia +1

The combination of the traditional convolutional network (i.e., an auto-encoder) and the graph convolutional network has attracted much attention in clustering, in which the auto-e…

cs.CV2021

Superpixel-guided Discriminative Low-rank Representation of Hyperspectral Images for Classification

Shujun Yang, Junhui Hou, Yuheng Jia +2

In this paper, we propose a novel classification scheme for the remotely sensed hyperspectral image (HSI), namely SP-DLRR, by comprehensively exploring its unique characteristics,…

cs.LG20212 cited

Self-supervised Symmetric Nonnegative Matrix Factorization

Yuheng Jia, Hui Liu, Junhui Hou +2

Symmetric nonnegative matrix factorization (SNMF) has demonstrated to be a powerful method for data clustering. However, SNMF is mathematically formulated as a non-convex optimizat…

cs.LG20201 cited

Clustering Ensemble Meets Low-rank Tensor Approximation

Yuheng Jia, Hui Liu, Junhui Hou +1

This paper explores the problem of clustering ensemble, which aims to combine multiple base clusterings to produce better performance than that of the individual one. The existing…

cs.CV2020

Superpixel Segmentation Based on Spatially Constrained Subspace Clustering

Hua Li, Yuheng Jia, Runmin Cong +3

Superpixel segmentation aims at dividing the input image into some representative regions containing pixels with similar and consistent intrinsic properties, without any prior know…