Zobrazeno 1 - 10
of 128 624
pro vyhledávání: '"DRM"'
Autor:
ŞAHİN, Gökhan1 gsahin@ktu.edu.tr
Publikováno v:
Journal of Marmara University Social Sciences Institute / Öneri. tem2024, Vol. 19 Issue 62, p1-17. 17p.
Autor:
Elnour, Ahmed Y.1 (AUTHOR) aelnour@ksu.edu.sa, Abasaeed, Ahmed E.1 (AUTHOR) abasaeed@ksu.edu.sa, Fakeeha, Anis H.1 (AUTHOR) anishf@ksu.edu.sa, Ibrahim, Ahmed A.1 (AUTHOR) aidid@ksu.edu.sa, Alreshaidan, Salwa B.2 (AUTHOR) chem241@ksu.edu.sa, Al-Fatesh, Ahmed S.1 (AUTHOR) aidid@ksu.edu.sa
Publikováno v:
Catalysts (2073-4344). Oct2024, Vol. 14 Issue 10, p721. 20p.
In this work, we address a foundational question in the theoretical analysis of the Deep Ritz Method (DRM) under the over-parameteriztion regime: Given a target precision level, how can one determine the appropriate number of training samples, the ke
Externí odkaz:
http://arxiv.org/abs/2407.09032
In the dynamic realm of digital content, safeguarding intellectual property rights poses critical challenges. This paper presents "SecureRights," an innovative Blockchain-based Trusted Digital Rights Management (DRM) framework. It strengthens the def
Externí odkaz:
http://arxiv.org/abs/2403.06094
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Yun, Jian1 (AUTHOR) yunjianm@163.com, Liu, Xinyu1 (AUTHOR), Lu, Yusheng1 (AUTHOR), Guan, Jingdan1 (AUTHOR), Liu, Xinyang1 (AUTHOR)
Publikováno v:
PLoS ONE. 9/19/2024, Vol. 19 Issue 9, p1-28. 28p.
Multiple news sources over the years have reported on the problematic effects of Digital Rights Management, yet there are no reforms for DRM development, simply removal. The issues are well-known to the public, frequently repeated even when addressed
Externí odkaz:
http://arxiv.org/abs/2311.06671
Autor:
Xu, Guowei, Zheng, Ruijie, Liang, Yongyuan, Wang, Xiyao, Yuan, Zhecheng, Ji, Tianying, Luo, Yu, Liu, Xiaoyu, Yuan, Jiaxin, Hua, Pu, Li, Shuzhen, Ze, Yanjie, Daumé III, Hal, Huang, Furong, Xu, Huazhe
Visual reinforcement learning (RL) has shown promise in continuous control tasks. Despite its progress, current algorithms are still unsatisfactory in virtually every aspect of the performance such as sample efficiency, asymptotic performance, and th
Externí odkaz:
http://arxiv.org/abs/2310.19668
Publikováno v:
American Journal of Psychology, 2020 Mar 01. 133(1), 49-62.
Externí odkaz:
https://www.jstor.org/stable/10.5406/amerjpsyc.133.1.0049