Zobrazeno 1 - 10
of 781
pro vyhledávání: '"Chen Yanyu"'
Autor:
Wang Jingwen, Wang Jingxin, Zhu Ye, Zhu Yan, Liu Caozhi, Chen Yanyu, Zeng Fanli, Chen Su, Wang Yucheng
Publikováno v:
BMC Plant Biology, Vol 23, Iss 1, Pp 1-11 (2023)
Abstract Background Identification of the motifs bound by a transcription factor (TF) is important to reveal the function of TF. Previously, we built a transcription factor centered yeast one hybrid (TF-Centered Y1H) that could identify the motifs bo
Externí odkaz:
https://doaj.org/article/b9d9b74cac9e41bbb23797eb51efd4d2
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-8 (2022)
Abstract The aim of this study is to demonstrate the feasibility of a commercially available Auto-Planning module for the radiation therapy treatment planning for locally advanced nasopharyngeal carcinoma (NPC). 22 patients with locally advanced NPC
Externí odkaz:
https://doaj.org/article/de463acaa77e49b1ba8f7302ba3bb8a3
Autor:
Chen, Yanyu, Huang, Ganhong
Efficiently deploying large language models (LLMs) in real-world scenarios remains a critical challenge, primarily due to hardware heterogeneity, inference framework limitations, and workload complexities.Efficiently deploying large language models (
Externí odkaz:
http://arxiv.org/abs/2412.04788
We consider the problem of constructing distributed overlay networks, where nodes in a reconfigurable system can create or sever connections with nodes whose identifiers they know. Initially, each node knows only its own and its neighbors' identifier
Externí odkaz:
http://arxiv.org/abs/2412.04771
Bonne and Censor-Hillel (ICALP 2019) initiated the study of distributed subgraph finding in dynamic networks of limited bandwidth. For the case where the target subgraph is a clique, they determined the tight bandwidth complexity bounds in nearly all
Externí odkaz:
http://arxiv.org/abs/2411.11544
Autor:
Zhou, Jiahang, Chen, Yanyu, Hong, Zicong, Chen, Wuhui, Yu, Yue, Zhang, Tao, Wang, Hui, Zhang, Chuanfu, Zheng, Zibin
Foundation models (e.g., ChatGPT, DALL-E, PengCheng Mind, PanGu-$\Sigma$) have demonstrated extraordinary performance in key technological areas, such as natural language processing and visual recognition, and have become the mainstream trend of arti
Externí odkaz:
http://arxiv.org/abs/2401.02643
Publikováno v:
Industrial Management & Data Systems, 2024, Vol. 124, Issue 12, pp. 3298-3323.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IMDS-10-2023-0747
Understanding videos is an important research topic for multimodal learning. Leveraging large-scale datasets of web-crawled video-text pairs as weak supervision has become a pre-training paradigm for learning joint representations and showcased remar
Externí odkaz:
http://arxiv.org/abs/2311.12919
Data sparsity and cold-start problems are persistent challenges in recommendation systems. Cross-domain recommendation (CDR) is a promising solution that utilizes knowledge from the source domain to improve the recommendation performance in the targe
Externí odkaz:
http://arxiv.org/abs/2311.02398
Convolutional neural network (CNN) models have seen advanced improvements in performance in various domains, but lack of interpretability is a major barrier to assurance and regulation during operation for acceptance and deployment of AI-assisted app
Externí odkaz:
http://arxiv.org/abs/2211.00185