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

Associative Learning

Associative Learning

Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...

Multi-input and Multi-variable systems

Multi-input and Multi-variable systems

Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...

Law of Independent Assortment

Law of Independent Assortment

While Mendel’s Law of Segregation states that the two alleles for one gene are separated into different gametes, a different question of how different genes are inherited remains. For example, is the gene for tall plants inherited with the gene for green peas? Mendel asked this question by experimenting with a dihybrid cross; a cross in which both parents are homozygous for two distinct traits resulting in an F1 generation that are heterozygous for both traits.

Labeling DNA Probes

Labeling DNA Probes

DNA probes are fragments of DNA labeled with a reporter tag to enable their detection or purification. The resulting labeled DNA probes can then hybridize to target nucleic acid sequences through complementary base-pairing, and may be used to recover or identify these regions.
Radioisotopes, fluorophores, or small molecule binding partners like biotin or digoxigenin, are the most widely used reporter tags for labeling DNA probes. These labels can be attached to the probe DNA molecule via...

You might also read

Related Articles

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

Sort by

Same author

Evaluating the prognostic value of body mass index in diffuse large B-cell lymphoma: a systematic review and meta-analysis.

Frontiers in nutrition·2026

Same author

2D Amorphous MoO<sub>3-x</sub>/Ti<sub>3</sub>C<sub>2</sub>T<sub>x</sub> MXene Heterostructure: Interface Charge Transfer-Induced Carbon Defect-Driven Enhancement of Ferromagnetism.

Small (Weinheim an der Bergstrasse, Germany)·2026

Same author

Ultrasound-Activatable Piezoelectric Hydrogel Reprograms Mitochondrial Epigenetics for Osteoarthritis Therapy via the mTOR/GATD3A Axis.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026

Same author

Air Instability-Induced Mechanical Degradation Plaguing Cyclability of Polycrystalline Nickel-Rich Layered Cathode.

Journal of the American Chemical Society·2026

Same author

Immunoengineering in the field of tendon and bone regeneration: immunomodulatory biomaterials, delivery platforms, and preclinical models for chronic diseases.

Frontiers in bioengineering and biotechnology·2026

Same author

Leucyl tRNA synthetase ameliorates cholestatic liver injury by inhibiting integrated stress response in mice.

Scientific reports·2026

Search research articles

Related Experiment Video

Updated: Jun 11, 2025

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

Self-adaptive label discovery and multi-view fusion for complementary label learning.

Long Tang¹, Pengfei Yan², Yingjie Tian³

¹School of Artificial Intelligence, Nanjing University of Information Science & Technology, Nanjing, 210044, China; Research Institute of Talent Big Data, Nanjing University of Information Science & Technology, Nanjing, 210044, China.

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

|October 8, 2024

Summary

This summary is machine-generated.

This study introduces a new complementary label learning (CLL) method (MVSLDCLL) that improves accuracy by discovering better label distributions and fusing multi-view features. The approach enhances performance in weak supervision scenarios.

Keywords:

Complementary label learning Machine learning Multi-view learning Self-adaptive label discovery Semi-supervised learning

More Related Videos

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

Published on: April 10, 2016

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: Jun 11, 2025

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

Published on: April 10, 2016

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
Computer Science
Artificial Intelligence

Background:

Complementary label learning (CLL) is a weak supervision framework reducing labeling burden by excluding incorrect labels.
Traditional CLL methods often face performance decline due to weakened supervised information.

Purpose of the Study:

To propose a novel multi-view fusion and self-adaptive label discovery based CLL method (MVSLDCLL).
To enhance classification accuracy in CLL by addressing the limitations of weakened supervision.

Main Methods:

Employed graph-based semi-supervised learning for self-adaptive label discovery, representing label distributions as convex combinations.
Implemented a multi-view fusion module to align feature representations by minimizing projection discrepancies between views.
Introduced a mechanism to incorporate view-discrepancy inspired by teamwork.

Main Results:

MVSLDCLL demonstrated the ability to learn more discriminative label distributions.
Achieved significantly higher accuracies compared to existing state-of-the-art CLL methods.
Ablation studies confirmed the effectiveness of both self-adaptive label discovery and multi-view fusion components.

Conclusions:

The proposed MVSLDCLL method effectively overcomes performance limitations in complementary label learning.
The integration of self-adaptive label discovery and multi-view fusion offers a robust solution for weak supervision tasks.