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Updated: Jun 23, 2026

Fine-tuning the Size and Minimizing the Noise of Solid-state Nanopores
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Published on: October 31, 2013

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统一和重新审视度意识最小化与噪音注入微批次调度器,以提高效率

Zheng Wei1, Xingjun Zhang1, Zhendong Tan1

  • 1School of Computer Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China.

Neural networks : the official journal of the International Neural Network Society
|February 8, 2025
PubMed
概括

敏度意识最小化 (SAM) 提高了概括性,但在计算上是昂贵的. 本研究介绍了一种噪音注入方法,以提高SAM的效率和准确性,通过更快的培训实现竞争性结果.

关键词:
对抗性的训练是对抗性的训练.有效的学习算法.一般化 一般化 一般化敏度感知最小化的最小化

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