Zobrazeno 1 - 10
of 115
pro vyhledávání: '"Liao, Yiwen"'
Post-silicon validation is one of the most critical processes in modern semiconductor manufacturing. Specifically, correct and deep understanding in test cases of manufactured devices is key to enable post-silicon tuning and debugging. This analysis
Externí odkaz:
http://arxiv.org/abs/2209.15249
Feature selection has drawn much attention over the last decades in machine learning because it can reduce data dimensionality while maintaining the original physical meaning of features, which enables better interpretability than feature extraction.
Externí odkaz:
http://arxiv.org/abs/2209.12282
In post-silicon validation, tuning is to find the values for the tuning knobs, potentially as a function of process parameters and/or known operating conditions. In this sense, an more efficient tuning requires identifying the most critical tuning kn
Externí odkaz:
http://arxiv.org/abs/2207.00336
Intelligent test requires efficient and effective analysis of high-dimensional data in a large scale. Traditionally, the analysis is often conducted by human experts, but it is not scalable in the era of big data. To tackle this challenge, variable s
Externí odkaz:
http://arxiv.org/abs/2207.00335
Autor:
Li, Xudong, Yang, Weijia, Liao, Yiwen, Zhang, Shushu, Zheng, Yang, Zhao, Zhigao, Tang, Maojia, Cheng, Yongguang, Liu, Pan
Publikováno v:
In Applied Energy 15 April 2024 360
Autor:
Liao, Yiwen, Xie, Qinghui, Yin, Xiaona, Li, Xiaoxiao, Xie, Junhui, Wu, Xingzhong, Tang, Sanmei, Liu, Mingjing, Zeng, Lihong, Pan, Yuying, Yang, Jianjiang, Feng, Zhanqin, Qin, Xiaolin, Zheng, Heping
Publikováno v:
In International Journal of Antimicrobial Agents April 2024 63(4)
With the high requirements of automation in the era of Industry 4.0, anomaly detection plays an increasingly important role in higher safety and reliability in the production and manufacturing industry. Recently, autoencoders have been widely used as
Externí odkaz:
http://arxiv.org/abs/2103.04662
Publikováno v:
In Journal of Membrane Science 5 January 2024 689
Feature selection is generally used as one of the most important preprocessing techniques in machine learning, as it helps to reduce the dimensionality of data and assists researchers and practitioners in understanding data. Thereby, by utilizing fea
Externí odkaz:
http://arxiv.org/abs/2010.13631
Akademický článek
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