Discriminatively Constrained Semi-supervised Multi-view Nonnegative Matrix Factorization with Graph Regularization

10/26/2020
by   Guosheng Cui, et al.
0

In recent years, semi-supervised multi-view nonnegative matrix factorization (MVNMF) algorithms have achieved promising performances for multi-view clustering. While most of semi-supervised MVNMFs have failed to effectively consider discriminative information among clusters and feature alignment from multiple views simultaneously. In this paper, a novel Discriminatively Constrained Semi-Supervised Multi-View Nonnegative Matrix Factorization (DCS^2MVNMF) is proposed. Specifically, a discriminative weighting matrix is introduced for the auxiliary matrix of each view, which enhances the inter-class distinction. Meanwhile, a new graph regularization is constructed with the label and geometrical information. In addition, we design a new feature scale normalization strategy to align the multiple views and complete the corresponding iterative optimization schemes. Extensive experiments conducted on several real world multi-view datasets have demonstrated the effectiveness of the proposed method.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
12/02/2020

Partially Shared Semi-supervised Deep Matrix Factorization with Multi-view Data

Since many real-world data can be described from multiple views, multi-v...
research
11/11/2018

Semi-supervised Deep Representation Learning for Multi-View Problems

While neural networks for learning representation of multi-view data hav...
research
02/28/2022

Semi-supervised Nonnegative Matrix Factorization for Document Classification

We propose new semi-supervised nonnegative matrix factorization (SSNMF) ...
research
03/02/2019

One-Pass Incomplete Multi-view Clustering

Real data are often with multiple modalities or from multiple heterogene...
research
05/01/2021

Multi-view Clustering via Deep Matrix Factorization and Partition Alignment

Multi-view clustering (MVC) has been extensively studied to collect mult...
research
01/08/2022

Multi-View Non-negative Matrix Factorization Discriminant Learning via Cross Entropy Loss

Multi-view learning accomplishes the task objectives of classification b...
research
09/08/2020

Dual-constrained Deep Semi-Supervised Coupled Factorization Network with Enriched Prior

Nonnegative matrix factorization is usually powerful for learning the "s...

Please sign up or login with your details

Forgot password? Click here to reset