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Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
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The mean absolute deviation is also a measure of the variability of data in a sample. It is the absolute value of the average difference between the data values and the mean.
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相关实验视频

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Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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信任意识的有条件对抗领域适应与特征规范对齐.

Jun Dan1, Tao Jin1, Hao Chi2

  • 1College of Information Science & Electronic Engineering, Zhejiang University, Hangzhou, 310027, China.

Neural networks : the official journal of the International Neural Network Society
|October 13, 2023
PubMed
概括

本研究介绍了信任意识的条件对抗域调整 (TCADA),以通过专注于样本可转移性和特征对齐来改善无监督域调整. TCADA提高了分类器的准确性和功能信息性,以更好地执行各种任务.

关键词:
域名适应领域适应特性规范 特性规范是指特征的规范.重新加权的对抗性培训转移学习转移学习可转让性 可转让性

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Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
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科学领域:

  • 计算机科学 计算机科学
  • 人工智能的人工智能
  • 机器学习 机器学习

背景情况:

  • 对抗性学习对于无监督的领域适应是有效的,但在样本可转移性和类别分布对齐方面存在困难.
  • 现有的方法往往忽略难以转移的样本,只能对准边际分布,导致分类器的不确定性.
  • 由于复杂的分布,直接匹配的特征规范可能是无效的,可能会降低特征.

研究的目的:

  • 开发一种新的信任意识条件对抗域调整 (TCADA) 方法.
  • 为了解决样本可转移性,类别分布对齐以及域调整中的特征规范差异的局限性.
  • 提高对目标数据的分类器的准确性和稳定性.

主要方法:

  • 量化数据可传输性使用后置概率模拟的高斯统一混合物.
  • 实施了以信任为指导的调整策略,用于精确的类别分布调整和共享特征学习.
  • 引入了基于运输的最佳策略,以调整功能规范并增强功能信息性.
  • 设计了一种混合信息引导的规范化术语,以改善分类器预测.

主要成果:

  • 拟议的TCADA方法显著提高了跨各种任务的转移性能.
  • TCADA有效地将条件分布和类别分布对齐,减少分类器的不确定性.
  • 最佳的运输策略成功地调整了特征规范,从而产生了更具信息性的共享特征.
  • 度规范化促进了特征与决策边界的分离,提高了目标数据预测的准确性.

结论:

  • 通过解决样本可转移性和特征对齐方面的关键挑战,TCADA为无监督域调整提供了强大的解决方案.
  • 该方法与现有方法相比,表现优越,特别是在具有复杂特征分布的场景中.
  • TCADA为目标域数据提供了更准确,更可靠的预测,展示了其实际实用性.