Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Jiaji Huang"'
Publikováno v:
Zhongguo quanke yixue, Vol 27, Iss 07, Pp 834-842 (2024)
Background Since the outbreak of COVID-19 infection, community medical personnel on the front lines of prevention and control of COVID-19 face the risk of direct contact with the virus, as well as problems such as high-intensity work, long working ho
Externí odkaz:
https://doaj.org/article/fca83f9ec66d4a7c9d97af948f0db3c7
Autor:
Weixin Li, Xinyang Wang, Jiaji Huang, Min Zhao, Jiao Yang, Fang Luo, Bin Qiu, Jian Wang, Zhenyu Lin
Publikováno v:
Sensors & Diagnostics. 2:699-706
The 3D structure provided abundant reaction sites. The Z-scheme has stronger redox ability and more efficient charge transfer. The AuNPs greatly reinforce vector electron transfer in the Z-scheme heterojunction.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::292c034810cd50a26ff339adee6c69ad
https://doi.org/10.1039/d3sd00040k
https://doi.org/10.1039/d3sd00040k
Publikováno v:
2021 International Conference on Data Mining Workshops (ICDMW).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c792cdabe80c60e3a4aec4c97d6f11aa
https://doi.org/10.1109/icdmw53433.2021.00087
https://doi.org/10.1109/icdmw53433.2021.00087
Publikováno v:
ICASSP
Language models (LM) have been widely deployed in modern ASR systems. The LM is often trained by minimizing its perplexity on speech transcript. However, few studies try to discriminate a "gold" reference against inferior hypotheses. In this work, we
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fb7d72657e832bb04f684311b789620c
https://doi.org/10.1109/icassp39728.2021.9414724
https://doi.org/10.1109/icassp39728.2021.9414724
Publikováno v:
NAACL-HLT
Multi-layer multi-head self-attention mechanism is widely applied in modern neural language models. Attention redundancy has been observed among attention heads but has not been deeply studied in the literature. Using BERT-base model as an example, t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a3b59bb31e4e175f7d0bea0bbbb6ce94
https://doi.org/10.18653/v1/2021.naacl-main.72
https://doi.org/10.18653/v1/2021.naacl-main.72
Publikováno v:
INTERSPEECH
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8b9724366c722161879886ff9924bab7
https://doi.org/10.21437/interspeech.2020-2516
https://doi.org/10.21437/interspeech.2020-2516
Publikováno v:
EMNLP (1)
This paper designs a Monolingual Lexicon Induction task and observes that two factors accompany the degraded accuracy of bilingual lexicon induction for rare words. First, a diminishing margin between similarities in low frequency regime, and secondl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2a99d521b485b1181dfaeee20e239311
https://doi.org/10.18653/v1/2020.emnlp-main.100
https://doi.org/10.18653/v1/2020.emnlp-main.100
Publikováno v:
ACL (1)
Bilingual Lexicon Induction (BLI) is the task of translating words from corpora in two languages. Recent advances in BLI work by aligning the two word embedding spaces. Following that, a key step is to retrieve the nearest neighbor (NN) in the target
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8b5ae80c9e04958e009c041baa1c258a
https://doi.org/10.18653/v1/p19-1399
https://doi.org/10.18653/v1/p19-1399
Autor:
Jiaji Huang, Kenneth Church, Md. Mostofa Ali Patwary, Milind Chabbi, Gregory Diamos, Heewoo Jun
Publikováno v:
IPDPS
We show how Zipf's Law can be used to scale up language modeling (LM) to take advantage of more training data and more GPUs. LM plays a key role in many important natural language applications such as speech recognition and machine translation. Scali
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2358b96a50c59c501cef4feae411f206
http://arxiv.org/abs/1810.10045
http://arxiv.org/abs/1810.10045
Publikováno v:
EMNLP
We propose a large margin criterion for training neural language models. Conventionally, neural language models are trained by minimizing perplexity (PPL) on grammatical sentences. However, we demonstrate that PPL may not be the best metric to optimi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::779fb4671d7583a2a10da4493aebab62
https://doi.org/10.18653/v1/d18-1150
https://doi.org/10.18653/v1/d18-1150