While many existing graph neural networks (GNNs) have been proven to perform $\ell_2 $- based graph smoothing that enforces smoothness globally, in this work we aim to further …
X Peng, J Feng, S Xiao, WY Yau… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Existing subspace clustering methods typically employ shallow models to estimate underlying subspaces of unlabeled data points and cluster them into corresponding groups …
Most popular clustering methods map raw image data into a projection space in which the clustering assignment is obtained with the vanilla k-means approach. In this article, we …
Subspace clustering aims to cluster unlabeled samples into multiple groups by implicitly seeking a subspace to fit each group. Most of existing methods are based on a shallow …
C Cui, Y Ren, J Pu, J Li, X Pu, T Wu… - Advances in Neural …, 2024 - proceedings.neurips.cc
Multi-view clustering (MVC) is a popular technique for improving clustering performance using various data sources. However, existing methods primarily focus on acquiring …
In this paper, we examine the main advances registered in the last ten years in Pattern Recognition methodologies based on graph matching and related techniques, analyzing …
E Kodirov, T Xiang, Z Fu, S Gong - … The Netherlands, October 11–14, 2016 …, 2016 - Springer
Most existing person re-identification (Re-ID) methods are based on supervised learning of a discriminative distance metric. They thus require a large amount of labelled training image …
J Huang, F Nie, H Huang - Proceedings of the AAAI Conference on …, 2013 - ojs.aaai.org
Spectral clustering has been a popular data clustering algorithm. This category of approaches often resort to other clustering methods, such as K-Means, to get the final …
Recently, nuclear norm-based low rank representation (LRR) methods have been popular in several applications, such as subspace segmentation. However, there exist two limitations …