Subspace Clustering

Subspace clustering aims to group data points based on their underlying low-dimensional subspace affiliations, addressing the challenge of clustering high-dimensional data. Current research focuses on developing robust algorithms, often incorporating graph convolutional networks, deep learning architectures (like autoencoders), and techniques like ADMM unfolding, to improve clustering accuracy and efficiency, particularly for noisy or multi-view data. These advancements are significant for various applications, including image segmentation, molecular dynamics analysis, and hyperspectral image processing, where identifying underlying structures within complex datasets is crucial. The development of more efficient and robust subspace clustering methods continues to be a key area of investigation.

Papers

November 17, 2024

Spectral Subspace Clustering for Attributed Graphs
Xiaoyang Lin, Renchi Yang, Haoran Zheng, Xiangyu Ke
Spectral Clustering Subspace Clustering Self Expressive Attributed Graph L SVRG

September 24, 2024

Self-Supervised Graph Embedding Clustering
Fangfang Li, Quanxue Gao, Cheng Deng, Wei Xia
Dimensionality Reduction K Mean Subspace Clustering Self Supervised Graph Centroid Based Clustering

September 4, 2024

Diffusion Models Learn Low-Dimensional Distributions via Subspace Clustering
Peng Wang, Huijie Zhang, Zekai Zhang, Siyi Chen, Yi Ma, Qing Qu
Diffusion Model Low Rank Subspace Clustering Denoising Autoencoder Image Distribution

August 19, 2024

Robust spectral clustering with rank statistics
Joshua Cape, Xianshi Yu, Jonquil Z. Liao
Spectral Clustering Subspace Clustering Block Model Rank Frequency

July 31, 2024

Temporal Subspace Clustering for Molecular Dynamics Data
Anna Beer, Martin Heinrigs, Claudia Plant, Ira Assent
Molecular Dynamic Subspace Clustering Subspace Prototype Molecular Dynamic Trajectory Order Markov

June 25, 2024

Principal Component Clustering for Semantic Segmentation in Synthetic Data Generation
Felix Stillger, Frederik Hasecke, Tobias Meisen
Semantic Segmentation Latent Diffusion Model Synthetic Data Generation Latent Diffusion Synthetic Video Subspace Clustering

June 6, 2024

Subspace Clustering in Wavelet Packets Domain
Ivica Kopriva, Damir Sersic
Subspace Clustering Subspace Learning Wavelet Domain Transform Domain

April 10, 2024

Unfolding ADMM for Enhanced Subspace Clustering of Hyperspectral Images
Xianlu Li, Nicolas Nadisic, Shaoguang Huang, Aleksandra Pižurica
Hyperspectral Image Deep Unfolding Subspace Clustering Alternating Direction Method of Multiplier Representation Matrix Sparse Subspace

March 3, 2024

Multiview Subspace Clustering of Hyperspectral Images based on Graph Convolutional Networks
Xianju Li, Renxiang Guan, Zihao Li, Hao Liu, Jing Yang
Hyperspectral Image Deep Subspace Subspace Clustering Multi View Subspace Clustering

January 30, 2024

December 25, 2023

Deep Structure and Attention Aware Subspace Clustering
Wenhao Wu, Weiwei Wang, Shengjiang Kong
Spectral Clustering Deep Clustering Unsupervised Representation Learning Subspace Clustering

December 11, 2023

Contrastive Multi-view Subspace Clustering of Hyperspectral Images based on Graph Convolutional Networks
Renxiang Guan, Zihao Li, Xianju Li, Chang Tang, Ruyi Feng
Hyperspectral Image Deep Subspace Subspace Clustering Affinity Matrix

September 15, 2023

Circular Clustering with Polar Coordinate Reconstruction
Xiaoxiao Sun, Paul Sajda
Clustering Algorithm Subspace Clustering State of the Art Clustering Polar Representation

June 23, 2023

Cascade Subspace Clustering for Outlier Detection
Qi Yang, Hao Zhu
Outlier Detection Subspace Clustering LOw Rank

June 20, 2023

Deep Double Self-Expressive Subspace Clustering
Ling Zhao, Yunpeng Ma, Shanxiong Chen, Jun Zhou
Spectral Clustering Deep Subspace Subspace Clustering Self Expressive

May 12, 2023

One-step Bipartite Graph Cut: A Normalized Formulation and Its Application to Scalable Subspace Clustering
Si-Guo Fang, Dong Huang, Chang-Dong Wang, Jian-Huang Lai
Application Proficiency Subspace Clustering New Formulation Graph Partitioning Graph Cut Laplacian Related Constraint Bipartite Graph Learning

May 5, 2023

Adaptive Graph Convolutional Subspace Clustering
Lai Wei, Zhengwei Chen, Jun Yin, Changming Zhu, Rigui Zhou, Jin Liu
Graph Convolution Deep Subspace Subspace Clustering Deep Graph Clustering

April 10, 2023

Monte Carlo Linear Clustering with Single-Point Supervision is Enough for Infrared Small Target Detection
Boyang Li, Yingqian Wang, Longguang Wang, Fei Zhang, Ting Liu, Zaiping Lin, Wei An, Yulan Guo
Data Detection Infrared Small Target Detection Subspace Clustering

March 14, 2023

High-dimensional multi-view clustering methods
Alaeddine Zahir, Khalide Jbilou, Ahmed Ratnani
Data Clustering High Dimension Multi View Clustering Subspace Clustering State of the Art Clustering Graph Based Clustering