Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Associative Learning01:27

Associative Learning

412
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...
412
Complementation Tests00:49

Complementation Tests

4.9K
A complementation test is a simple cross to identify whether the two mutations are located on the same gene or different genes. It was first performed by Edward Lewis in the 1940s while working on fruit flies. He developed the test to identify the location and arrangement of different mutations on chromosomes.
Organisms heterozygous for different mutations are crossed pairwise in all combinations. If present on different genes, the mutations can complement each other by providing the missing...
4.9K
Introduction to Learning01:18

Introduction to Learning

446
Learning is the process of acquiring knowledge or skills through practice or experience, leading to long-lasting behavioral changes. This acquisition occurs through interaction with the environment and requires practice or experience. For instance, mastering a skill such as surfing requires considerable practice and experience, highlighting the essential role of repeated interactions with the environment in learning.
In contrast to learned behaviors, unlearned behaviors such as crying, sexual...
446
Observational Learning01:12

Observational Learning

188
Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
188
Cognitive Learning01:21

Cognitive Learning

249
Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
249
Labeling Emotion01:20

Labeling Emotion

145
Emotional labeling is a cognitive process that involves identifying and naming one's emotions, such as anger, fear, happiness, or sadness. It allows individuals to recognize and express their internal emotional states, a critical aspect of emotional regulation and communication. Labeling emotions requires more than mere recognition; it also involves drawing upon memory and contextual cues to understand the current situation and apply a corresponding emotional label. For instance, feeling...
145

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Advances in GelMA Hydrogel-Enabled Angiogenic-Osteogenic Coupling: From Structural Programming to Exogenous Cue Synergy.

Journal of functional biomaterials·2026
Same author

Small-molecule modulation of β-arrestins.

Nature·2026
Same author

Rethinking Neonatal Surgical Urgency: Effective Delay with Internal Flow Restrictors.

The Annals of thoracic surgery·2026
Same author

The exocyst subunits OsEXO70L2 and OsSEC3A regulate root development through modulating OsPIN1a/b-mediated auxin distribution in rice.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Phosphorus-Free and Self-Extinguishing Cellulose Paper Achieved via Short-Chain Carboxylate-Functionalized Mn/Ni Nanoparticles.

ACS omega·2026
Same author

Acacetin ameliorates MASLD by inhibiting the Notch1 pathway in hepatocytes and reprogramming macrophage polarization via Keap1-Nrf2-mediated restraint of ferroptosis.

Metabolism: clinical and experimental·2026
Same journal

Dynamic analysis and reliable mechanical optimization application of ring HNN effected with a memristive neuron.

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

DAFF-Net: A detection and search method for small-scale low surface brightness galaxies.

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

Quasi-synchronization for complex networks with hybrid pinning intermittent control.

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

Physics-encoded convolutional neural operators for parametric PDEs: A convergence-guaranteed framework via pre-computed kernel fields.

Neural networks : the official journal of the International Neural Network Society·2026
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
查看所有相关文章

相关实验视频

Updated: Jul 12, 2025

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms
07:31

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms

Published on: February 8, 2019

6.6K

康科:补充监督的对比学习,用于补充标签学习.

Haoran Jiang1, Zhihao Sun2, Yingjie Tian3

  • 1School of Mathematical and Sciences, University of Chinese Academy of Sciences, Beijing, 100190, China; Research Center on Fictitious Economy and Data Science, University of Chinese Academy of Sciences, Beijing, 100190, China; Key Laboratory of Big Data Mining and Knowledge Management, University of Chinese Academy of Sciences, Beijing, 100190, China.

Neural networks : the official journal of the International Neural Network Society
|October 19, 2023
PubMed
概括
此摘要是机器生成的。

补充标签学习 (CLL) 得到了ComCo的改进,这是一种使用对比学习的新方法. 在CLL任务中,ComCo有效地利用在互补标签中的语义信息来实现更好的表示学习和更好的表现.

关键词:
补充的标签学习学习相反的学习学习.机器学习 机器学习代表性的学习学习.缺乏监督的学习学习.

更多相关视频

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

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

Published on: December 15, 2023

565
Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
08:25

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

9.0K

相关实验视频

Last Updated: Jul 12, 2025

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms
07:31

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms

Published on: February 8, 2019

6.6K
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

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

Published on: December 15, 2023

565
Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
08:25

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

9.0K

科学领域:

  • 机器学习 机器学习
  • 计算机科学 计算机科学

背景情况:

  • 补充标签学习 (CLL) 通过使用标签表示样本不是什么来降低数据标签成本.
  • 现有的CLL方法往往忽视了补充标签中的丰富的语义信息.
  • 尽管有潜在的好处,但CLL仍然是一个具有挑战性的问题.

研究的目的:

  • 引入ComCo,一种新的方法,通过结合对比学习来增强互补标签学习 (CLL).
  • 通过有效利用来自互补标签的语义信息来解决以前的CLL方法的局限性.

主要方法:

  • 康科采用针对CLL量身定制的对比学习框架.
  • 关键策略包括可靠的阳性样本的积极选择机制.
  • 负选择策略有效地利用补充标签信息来构建信息化的负集.

主要成果:

  • 康科展示了显著改善的代表性学习能力.
  • 拟议的方法优于基线模型和CLL当前最先进的方法.
  • 经验结果显示,在补充标签学习任务中,表现提高了高达14.61%.

结论:

  • 通过整合对比学习,ComCo提供了一种强大的新方法来补充标签学习.
  • 该方法在补充标签中利用语义信息的能力导致了卓越的性能.
  • 康科代表了机器学习领域的重大进步,用于具有成本效益的数据标签.