Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Stability of structures

Stability of structures

In mechanical engineering, the stability of systems under various forces is critical for designing durable and efficient structures. One fundamental way to explore these concepts is by analyzing systems like two rods connected at a pivot point, O, with a torsional spring of spring constant k at the pivot point. This system is similar in appearance to a scissor jack used to change tires on a car. In this case, the arms of the linkage (equivalent to the rods in this system) are entirely vertical,...

Vector Algebra: Method of Components

Vector Algebra: Method of Components

It is cumbersome to find the magnitudes of vectors using the parallelogram rule or using the graphical method to perform mathematical operations like addition, subtraction, and multiplication. There are two ways to circumvent this algebraic complexity. One way is to draw the vectors to scale, as in navigation, and read approximate vector lengths and angles (directions) from the graphs. The other way is to use the method of components.
In many applications, the magnitudes and directions of...

Upsampling

Upsampling

Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...

Extraction: Partition and Distribution Coefficients

Extraction: Partition and Distribution Coefficients

The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an...

Per-Unit Sequence Models

Per-Unit Sequence Models

An ideal Y-Y transformer, grounded through neutral impedances, displays per-unit sequence networks akin to those of a single-phase ideal transformer when subjected to balanced positive- or negative-sequence currents. These currents do not produce neutral currents, and their associated voltage drops.
Zero-sequence currents, which are identical in magnitude and phase, generate a neutral current, resulting in voltage drops across the neutral impedance and the low-voltage winding. If the...

Survival Tree

Survival Tree

Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
Building a Survival Tree
Constructing a...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Advanced Demodulation in Distributed Fiber Optic Sensing: A Review of Backscattering and UWFBG-Based Technologies.

Sensors (Basel, Switzerland)·2026

Same author

Enhanced anchor contrastive multi-view representations learning network for clustering.

Neural networks : the official journal of the International Neural Network Society·2025

Same author

Interrogation of a large-capacity densely spaced fiber Bragg grating array using chaos-based incoherent-optical frequency domain reflectometry.

Optics letters·2019

Same author

High-Density Distributed Crack Tip Sensing System Using Dense Ultra-Short FBG Sensors.

Sensors (Basel, Switzerland)·2019

Same author

Large-scale multiplexing of a FBG array with randomly varied characteristic parameters for distributed sensing.

Optics letters·2018

Same author

Determination of roxithromycin from human plasma samples based on magnetic surface molecularly imprinted polymers followed by liquid chromatography-tandem mass spectromer.

Journal of chromatography. B, Analytical technologies in the biomedical and life sciences·2015

Same journal

Exploiting audio-visual modalities in videos: Object detection via multi-stage bilateral coupling network.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

Reliability-aware modality completion with cross-modal distillation for federated learning with missing modalities.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

IGFD-Net: Illumination-guided frequency decoupling for polarization image fusion.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

Multiple-Strategies dung beetle optimizer and its applications in engineering optimization and bankruptcy prediction.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

Aggregating global-scale pixel-wise forgery cues within a graph.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

Finite-Time intermittent control for secure synchronization of Neutral-Type stochastic delayed neural networks under aperiodic DoS attacks.

Neural networks : the official journal of the International Neural Network Society·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jan 8, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

Robust structure-preservation tensorized representation for multi-view unsupervised feature selection.

Chen Wang¹, Peng Song¹, Changjia Wang¹

¹School of Computer and Control Engineering, Yantai University, Yantai, 264005, China.

Neural Networks : the Official Journal of the International Neural Network Society

|December 23, 2025

Summary

This summary is machine-generated.

This study introduces a robust structure-preservation tensorized representation (RSTR) for multi-view unsupervised feature selection (MUFS). RSTR effectively handles noisy data and optimizes view structures, outperforming existing methods.

Keywords:

Feature selection Multi-view learning Rank constraint Scaled simplex representation Tensor

More Related Videos

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

Related Experiment Videos

Last Updated: Jan 8, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

Area of Science:

Machine Learning
Data Mining
Computer Science

Background:

Self-representation methods construct affinity matrices for multi-view unsupervised feature selection (MUFS).
Existing methods are challenged by data noise, distorted relationships due to constraints, and suboptimal view structure exploitation.

Purpose of the Study:

To propose a novel robust structure-preservation tensorized representation (RSTR) method for MUFS.
To address limitations of existing methods in handling noise and optimizing view structures.

Main Methods:

RSTR decomposes affinity matrices into clean and noise components to reduce noise impact.
Introduces scaled simplex constraint for physically meaningful affinity matrices and inherent structure discovery.
Employs rank constraint to identify optimal view structures and constructs a weighted tensor to mine high-order relationships across views.

Main Results:

The proposed RSTR method demonstrates superior performance compared to state-of-the-art competitors.
Experiments on eight datasets validate the effectiveness of RSTR in improving MUFS.

Conclusions:

RSTR offers a robust and effective approach for multi-view unsupervised feature selection.
The method successfully mitigates noise, preserves inherent data structures, and optimizes view representations.