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

Quantifying Work02:30

Quantifying Work

19.1K
As a system undergoes a change, its internal energy can change, and energy can be transferred from the system to the surroundings, or from the surroundings to the system. 
19.1K
Modeling and Similitude01:12

Modeling and Similitude

246
Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
246

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

Multi-center validation of a machine learning model for early detection of monoclonal immunoglobulin-related disorders using routine laboratory data.

Frontiers in immunology·2026
Same author

Targeting androgen receptor transcriptionally represses VCP and enhances the efficacy of oncolytic-immunotherapy in hepatocellular carcinoma.

Pharmacological research·2026
Same author

Mitotic Cdc42 waves encode PI(3,4)P<sub>2</sub> signaling and Golgi morphological state to control spindle scaling.

Science advances·2026
Same author

Characterizing selection signatures in coding and noncoding regions of 14,886 cancer genomes.

Journal of genetics and genomics = Yi chuan xue bao·2026
Same author

Coordinated changes in microbiota features, short-chain fatty acids, and peripheral clocks accompany fructo-oligosaccharide-associated metabolic improvement.

Food & function·2026
Same author

[Impact of effective health information acquisition on hemophilia-related health literacy among caregivers of underage hemophilia patients].

Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences·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: Jun 9, 2025

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks
06:57

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks

Published on: August 9, 2016

11.3K

瓦斯斯坦任务嵌入用于测量任务相似性.

Xinran Liu1, Yikun Bai1, Yuzhe Lu2

  • 1Computer Science Department, Vanderbilt University, 2201 W End Ave, Nashville, 37235, TN, United States.

Neural networks : the official journal of the International Neural Network Society
|October 25, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的,不依赖模型的方法,用于测量机器学习中的任务相似性,使用最佳运输理论. 这种方法可以实现更快,更有效的任务比较,这对于转移和元学习应用至关重要.

关键词:
持续的学习 持续的学习数据集的相似性数据集的相似性最佳的运输方式任务嵌入式 任务嵌入式转移学习转移学习

更多相关视频

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.4K
The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups
14:14

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups

Published on: May 13, 2022

5.8K

相关实验视频

Last Updated: Jun 9, 2025

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks
06:57

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks

Published on: August 9, 2016

11.3K
A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.4K
The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups
14:14

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups

Published on: May 13, 2022

5.8K

科学领域:

  • 机器学习 机器学习
  • 计算机科学 计算机科学
  • 数据科学数据科学数据科学

背景情况:

  • 测量任务相似性对于机器学习任务如转移,多任务,连续和元学习至关重要.
  • 现有的任务相似性评估方法通常依赖于架构,依赖于预先训练的模型或前向转移代理.
  • 这些局限性阻碍了跨不同机器学习范式的高效和可概括的任务比较.

研究的目的:

  • 为监督分类引入一种新的,与模型无关的,不需要培训的任务嵌入方法.
  • 解决当前基于架构的方法测量任务相似性的局限性.
  • 为了能够有效地处理部分分离的标签集的数据集.

主要方法:

  • 利用最佳运输理论来定义监督分类的新任务嵌入.
  • 采用多维缩放用于标签嵌入,然后与数据集样本连接.
  • 定义数据集距离,使用更新样本之间的2-瓦瑟斯坦距离.
  • 使用2-瓦瑟斯坦嵌入框架将任务映射到矢量空间中.

主要成果:

  • 建议的任务嵌入是无模型和无培训的,能够处理不连接的标签集.
  • 使用新型嵌入的任务比较比现有的方法要快得多,比如最佳运输数据集距离 (OTDD).
  • 数字实验表明,在图像识别数据集中,拟议的距离和前向/后向传输之间存在统计学上显著的相关性.

结论:

  • 开发的2-Wasserstein嵌入框架为测量任务相似性提供了一种高效和有效的方法.
  • 这种模型不可知的方法通过提供一个更可概括的工具来进行任务比较来推进机器学习领域.
  • 这些发现对提高转移学习,多任务学习和超级学习应用中的性能有影响.