Zobrazeno 1 - 10
of 306
pro vyhledávání: '"Gao, Boyan"'
Autor:
Zhang, Bo-Wen, Wang, Liangdong, Li, Jijie, Gu, Shuhao, Wu, Xinya, Zhang, Zhengduo, Gao, Boyan, Ao, Yulong, Liu, Guang
This paper introduces the Aquila2 series, which comprises a wide range of bilingual models with parameter sizes of 7, 34, and 70 billion. These models are trained based on an innovative framework named HeuriMentor (HM), which offers real-time insight
Externí odkaz:
http://arxiv.org/abs/2408.07410
Utilizing large pre-trained models for specific tasks has yielded impressive results. However, fully fine-tuning these increasingly large models is becoming prohibitively resource-intensive. This has led to a focus on more parameter-efficient transfe
Externí odkaz:
http://arxiv.org/abs/2408.02421
Autor:
Xing, Xingrun, Gao, Boyan, Zhang, Zheng, Clifton, David A., Xiao, Shitao, Du, Li, Li, Guoqi, Zhang, Jiajun
The recent advancements in large language models (LLMs) with billions of parameters have significantly boosted their performance across various real-world applications. However, the inference processes for these models require substantial energy and
Externí odkaz:
http://arxiv.org/abs/2407.04752
Optimisers are an essential component for training machine learning models, and their design influences learning speed and generalisation. Several studies have attempted to learn more effective gradient-descent optimisers via solving a bi-level optim
Externí odkaz:
http://arxiv.org/abs/2203.02711
Publikováno v:
In Food Hydrocolloids January 2025 158
Chemical Compositions of Lianqiao (Forsythia suspensa) Extracts and Their Potential Health Benefits.
Autor:
Gao, Boyan1 (AUTHOR) gaoboyan@sjtu.edu.cn, Zhu, Hanshu1 (AUTHOR) zhuhanshu@sjtu.edu.cn, Liu, Zhihao2,3 (AUTHOR) jianghao.sun@usda.gov, He, Xiaohua4 (AUTHOR) xiaohua.he@usda.gov, Sun, Jianghao3 (AUTHOR) xianli.wu@usda.gov, Li, Yanfang2 (AUTHOR) yfl0820@umd.edu, Wu, Xianli3 (AUTHOR) pamela.pehrsson@usda.gov, Pehrsson, Pamela3 (AUTHOR), Zhang, Yaqiong1 (AUTHOR) yqzhang2006@sjtu.edu.cn, Yao, Yuanhang2 (AUTHOR) lyu5@umd.edu, Yu, Liangli2 (AUTHOR)
Publikováno v:
Pharmaceuticals (14248247). Jun2024, Vol. 17 Issue 6, p740. 17p.
Publikováno v:
In European Journal of Obstetrics & Gynecology and Reproductive Biology: X December 2024 24
Autor:
Zhang, Xiaowei, Yi, Xueer, Yu, Wenwen, Chen, Tingting, Gao, Boyan, Gilbert, Robert G., Li, Cheng
Publikováno v:
In Carbohydrate Polymers 1 April 2024 329
We present a "learning to learn" approach for automatically constructing white-box classification loss functions that are robust to label noise in the training data. We parameterize a flexible family of loss functions using Taylor polynomials, and ap
Externí odkaz:
http://arxiv.org/abs/2103.00243
Autor:
Fang, Shuaizhen, Liu, Wenwen, Zhang, Yaqiong, Li, Yanfang, Gao, Boyan, Yang, Puyu, Xie, Zhuohong, Yu, Liangli (Lucy)
Publikováno v:
In Food Hydrocolloids January 2024 146 Part A