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相关概念视频

Stereotypes, Prejudice, and Discrimination02:55

Stereotypes, Prejudice, and Discrimination

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Humans are very diverse and although we share many similarities, we also have many differences. The social groups we belong to help form our identities (Tajfel, 1974). These differences may be difficult for some people to reconcile, which may lead to prejudice toward people who are different. Prejudice is a negative attitude and feeling toward an individual based solely on one’s membership in a particular social group (Allport, 1954; Brown, 2010). Prejudice is common against people who...
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Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
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The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
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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...
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In situ hybridization (ISH) is a technique used to detect and localize specific DNA or RNA molecules in cells, tissue, or tissue sections using a labeled probe. The technique was first used in 1969 for the investigation of nucleic acids. It is currently an essential tool in scientific research and clinical settings, especially for diagnostic purposes.
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一种简单的基于插值的数据增强方法,用于隐式情绪识别.

Yuxia Zhao1,2,3, Mahpirat Mamat1,4, Alimjan Aysa1,4

  • 1School of Information Science and Engineering, Xinjiang University, Ürümqi, 830046, Xinjiang, China.

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概括
此摘要是机器生成的。

ISIMIX是一种新的数据增强方法,通过插入隐藏空间来解决隐含情绪识别方面的挑战. 这种方法有效地减轻了数据稀缺性,并改善了自然语言处理任务中的模型性能.

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科学领域:

  • 自然语言处理自然语言处理.
  • 机器学习 机器学习
  • 计算语言学 计算语言学

背景情况:

  • 隐含的情感识别在NLP中至关重要,但面临着语义复杂性和数据稀缺等挑战.
  • 深度学习模型因缺乏明确的情绪词和有限的注释数据而与隐含的情绪斗争.
  • 现有的数据增强方法往往缺乏有效性,并可能引入噪音.

研究的目的:

  • 提出一种有效的数据增强方法,用于隐式情绪识别.
  • 为了解决隐性情绪分析中的数据稀缺和过度匹配问题.
  • 提高模型在识别隐含情绪方面的表现.

主要方法:

  • 开发ISIMIX,一种基于插值的数据增强技术,在隐藏空间中运行.
  • 通过基础增强技术生成增强样本,并将其与原始数据混合.
  • 整合了Jensen-Shannon分歧规范化,以最大限度地减少原始和增强数据分布之间的差异.

主要成果:

  • 在隐式情绪识别中,ISIMIX有效地缓解了数据稀缺问题.
  • 与现有的数据增强技术相比,该方法表现出更高的性能.
  • 三个公共数据集的实验结果显示ISIMIX的性能优于主流的文本分类方法.

结论:

  • ISIMIX是一种简单但有效的隐性情绪识别方法.
  • 该方法显示了在NLP任务中广泛应用的巨大潜力.
  • 隐藏空间的插入为数据增强提供了有效和强大的解决方案.