Multi-View Spectral Clustering Tailored Tensor Low-Rank Representation

04/30/2020
by   Yuheng Jia, et al.
8

This paper explores the problem of multi-view spectral clustering (MVSC) based on tensor low-rank modeling. Unlike the existing methods that all adopt an off-the-shelf tensor low-rank norm without considering the special characteristics of the tensor in MVSC, we design a novel structured tensor low-rank norm tailored to MVSC. Specifically, the proposed norm explicitly imposes a symmetric low-rank constraint and a structured sparse low-rank constraint on the frontal and horizontal slices of the tensor to characterize the intra-view and inter-view relationships, respectively. Moreover, the two constraints are optimized at the same time to achieve mutual refinement. The proposed model is convex and efficiently solved by an augmented Lagrange multiplier based method. Extensive experimental results on 5 benchmark datasets show that the proposed method outperforms state-of-the-art methods to a significant extent. Impressively, our method is able to produce perfect clustering.

READ FULL TEXT

page 1

page 2

page 3

page 4

page 5

page 6

page 8

page 9

research
10/23/2016

On Unifying Multi-View Self-Representations for Clustering by Tensor Multi-Rank Minimization

In this paper, we address the multi-view subspace clustering problem. Ou...
research
01/02/2016

Tensor Sparse and Low-Rank based Submodule Clustering Method for Multi-way Data

A new submodule clustering method via sparse and low-rank representation...
research
12/16/2020

Clustering Ensemble Meets Low-rank Tensor Approximation

This paper explores the problem of clustering ensemble, which aims to co...
research
08/19/2016

Iterative Views Agreement: An Iterative Low-Rank based Structured Optimization Method to Multi-View Spectral Clustering

Multi-view spectral clustering, which aims at yielding an agreement or c...
research
04/22/2023

Hyper-Laplacian Regularized Concept Factorization in Low-rank Tensor Space for Multi-view Clustering

Tensor-oriented multi-view subspace clustering has achieved significant ...
research
05/21/2022

Semi-Supervised Subspace Clustering via Tensor Low-Rank Representation

In this letter, we propose a novel semi-supervised subspace clustering m...
research
04/10/2021

A Novel Unified Model for Multi-exposure Stereo Coding Based on Low Rank Tucker-ALS and 3D-HEVC

Display technology must offer high dynamic range (HDR) contrast-based de...

Please sign up or login with your details

Forgot password? Click here to reset