Zobrazeno 1 - 10
of 1 713
pro vyhledávání: '"XU Xiaolin"'
Publikováno v:
陆军军医大学学报, Vol 46, Iss 9, Pp 997-1006 (2024)
Objective To explore the regulatory and functional mechanism of angiopoietin-like 4 (ANGPTL4) expression in gastric epithelial cells infected with Helicobacter pylori (H.pylori). Methods H.pylori-positive gastric specimens from Department of Gastroen
Externí odkaz:
https://doaj.org/article/fc1632b6539141d6968c611a22ab17ae
Publikováno v:
Fenmo yejin jishu, Vol 41, Iss 5, Pp 449-456, 480 (2023)
The formation mechanism and process control of the common defects in selective laser melting GH4169 alloys were briefly introduced, such as spheroidization and holes. The effects of laser power, scanning rate, and powder thickness on the microstructu
Externí odkaz:
https://doaj.org/article/388c47e0390b4944acd1e57e121b357f
Adapting pre-trained deep learning models to customized tasks has become a popular choice for developers to cope with limited computational resources and data volume. More specifically, probing--training a downstream head on a pre-trained encoder--ha
Externí odkaz:
http://arxiv.org/abs/2411.12508
At the forefront of control techniques is Model Predictive Control (MPC). While MPCs are effective, their requisite to recompute an optimal control given a new state leads to sparse response to the system and may make their implementation infeasible
Externí odkaz:
http://arxiv.org/abs/2410.16173
Graph-structured data is integral to many applications, prompting the development of various graph representation methods. Graph autoencoders (GAEs), in particular, reconstruct graph structures from node embeddings. Current GAE models primarily utili
Externí odkaz:
http://arxiv.org/abs/2410.03396
Autor:
Liu, Jun, Yuan, Geng, Zeng, Weihao, Tang, Hao, Zhang, Wenbin, Lin, Xue, Xu, XiaoLin, Huang, Dong, Wang, Yanzhi
Publikováno v:
Springer Nature - Book Series: Transactions on Computational Science & Computational Intelligence, 2022
In research findings, co-deletion of the 1p/19q gene is associated with clinical outcomes in low-grade gliomas. The ability to predict 1p19q status is critical for treatment planning and patient follow-up. This study aims to utilize a specially MRI-b
Externí odkaz:
http://arxiv.org/abs/2409.19583
Private inference (PI) has emerged as a promising solution to execute computations on encrypted data, safeguarding user privacy and model parameters in edge computing. However, existing PI methods are predominantly developed considering constant reso
Externí odkaz:
http://arxiv.org/abs/2407.05633
Text watermarks for large language models (LLMs) have been commonly used to identify the origins of machine-generated content, which is promising for assessing liability when combating deepfake or harmful content. While existing watermarking techniqu
Externí odkaz:
http://arxiv.org/abs/2406.01946
Autor:
Duan, Shijin, Wang, Chenghong, Peng, Hongwu, Luo, Yukui, Wen, Wujie, Ding, Caiwen, Xu, Xiaolin
As privacy-preserving becomes a pivotal aspect of deep learning (DL) development, multi-party computation (MPC) has gained prominence for its efficiency and strong security. However, the practice of current MPC frameworks is limited, especially when
Externí odkaz:
http://arxiv.org/abs/2406.02629
Publikováno v:
DAC2024
Trusted Execution Environments (TEEs) have become a promising solution to secure DNN models on edge devices. However, the existing solutions either provide inadequate protection or introduce large performance overhead. Taking both security and perfor
Externí odkaz:
http://arxiv.org/abs/2405.03974