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相关概念视频

Survival Tree01:19

Survival Tree

369
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...
369
Quantifying and Rejecting Outliers: The Grubbs Test01:02

Quantifying and Rejecting Outliers: The Grubbs Test

3.4K
Sometimes, a data set can have a recorded numerical observation that greatly  deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier.  To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This...
3.4K
Woodward–Hoffmann Selection Rules and Microscopic Reversibility01:34

Woodward–Hoffmann Selection Rules and Microscopic Reversibility

3.7K
Electrocyclic reactions, cycloadditions, and sigmatropic rearrangements are concerted pericyclic reactions that proceed via a cyclic transition state. These reactions are stereospecific and regioselective. The stereochemistry of the products depends on the symmetry characteristics of the interacting orbitals and the reaction conditions. Accordingly, pericyclic reactions are classified as either symmetry-allowed or symmetry-forbidden. Woodward and Hoffmann presented the selection criteria for...
3.7K
Generalization, Discrimination, and Extinction01:24

Generalization, Discrimination, and Extinction

1.3K
Generalization, discrimination, and extinction are key concepts in operant conditioning that influence how behaviors are learned and maintained.
Generalization occurs when a behavior reinforced in one context is performed in similar situations. For instance, a student who studies diligently for calculus and receives excellent grades might apply the same study habits to psychology and history, expecting similar results. Generalization shows how learning in one setting can influence behavior in...
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相关实验视频

Updated: Jan 7, 2026

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
09:23

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Published on: August 16, 2017

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可以通过相互信息来解释BERT的结构化修剪.

Hanjuan Huang1, Hao-Jia Song2, Qiling Zhao3

  • 1College of Mechanical and Electrical Engineering, Wuyi University, Wuyishan 354300, China.

Entropy (Basel, Switzerland)
|December 24, 2025
PubMed
概括
此摘要是机器生成的。

我们开发了一种无监督的方法,有效地从变压器 (BERT) 模型中修剪双向编码器表示. 这种技术减少了模型尺寸,并提高了边缘设备的性能,而不需要重新训练.

关键词:
伯特压缩系统的压缩方式可以解释的可解释.这是相互信息的互惠.结构化的修剪.

相关实验视频

Last Updated: Jan 7, 2026

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09:23

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Published on: August 16, 2017

8.5K

科学领域:

  • 人工智能的人工智能
  • 自然语言处理自然语言处理.
  • 机器学习 机器学习

背景情况:

  • 从变压器 (BERT) 的双向编码器表示模型对于自然语言处理 (NLP) 是强大的,但对于边缘设备而言计算成本昂贵.
  • 现有的压缩方法往往需要大量的再培训或监督数据,限制了它们的适用性.

研究的目的:

  • 为BERT模型引入无监督,无再培训的结构化修剪计划.
  • 为了降低BERT在边缘设备上部署的计算成本和内存足迹.

主要方法:

  • 一个由相互信息 (MI) 指导的新型修剪方案,使用雷尼α级.
  • 开发一个具有表达意识的MI估计器和一个以原则为基础的内核带宽选择,以获得稳定,样本效率高的修剪信号.
  • 应用可解释AI可视化来理解功能和预测压缩后的变化.

主要成果:

  • 拟议的方法有效地消除了BERT中多余的单元,同时保持了代表性能力.
  • 压缩模型显示显著减少内存和延迟,适合商品硬件.
  • 跨基准的评估显示了最小的准确性损失,超越了无监督基线,并与监督方法竞争.

结论:

  • 无监督,无再培训的修剪方案提供了一种有效的方式来压缩BERT模型.
  • 这种方法有助于在资源有限的边缘设备上部署先进的NLP模型.
  • 该方法保持模型性能,并通过Explainable-AI.提供对压缩过程的见解.