Zobrazeno 1 - 10
of 221
pro vyhledávání: '"LUO Yuping"'
Publikováno v:
Xiehe Yixue Zazhi, Vol 15, Iss 1, Pp 42-44 (2024)
At present, all countries and regions providing palliative care service regard living wills and similar documents expressing personal wishes as the legal premise for carrying out this medical service. Defining the population receiving palliative care
Externí odkaz:
https://doaj.org/article/b7eb275eb79c4873bff7a23fe0eb66f3
Publikováno v:
In LWT 1 September 2024 207
Autor:
Liu, Yu, Zhang, Boning, Luo, Yuping, Wang, Yingwu, Li, Yongqiang, Sun, Jiankun, Jiang, Xuexing, Ma, Jun, Mao, Yong
Publikováno v:
In Vacuum September 2024 227
Safe reinforcement learning is a promising path toward applying reinforcement learning algorithms to real-world problems, where suboptimal behaviors may lead to actual negative consequences. In this work, we focus on the setting where unsafe states c
Externí odkaz:
http://arxiv.org/abs/2202.07789
Autor:
Li, Chun1,2 (AUTHOR), Luo, Yuping1,3 (AUTHOR), Li, Siguang1,3 (AUTHOR) lisiguang@tongji.edu.cn
Publikováno v:
Stem Cell Research & Therapy. 7/8/2024, Vol. 15 Issue 1, p1-13. 13p.
Autor:
Xiong, Weijie, Luo, Yuping, Shangguan, Wengao, Deng, Yue, Li, Ronghua, Song, Dan, Zhang, Muyuan, Li, Zengyi, Xiao, Ran
Publikováno v:
In Waste Management 15 December 2024 190:174-185
Autor:
Luo, Yuping, Ma, Tengyu
Training-time safety violations have been a major concern when we deploy reinforcement learning algorithms in the real world. This paper explores the possibility of safe RL algorithms with zero training-time safety violations in the challenging setti
Externí odkaz:
http://arxiv.org/abs/2108.01846
The virtuoso plays the piano with passion, poetry and extraordinary technical ability. As Liszt said (a virtuoso)must call up scent and blossom, and breathe the breath of life. The strongest robots that can play a piano are based on a combination of
Externí odkaz:
http://arxiv.org/abs/2106.02040
Matrix factorization is a simple and natural test-bed to investigate the implicit regularization of gradient descent. Gunasekar et al. (2017) conjectured that Gradient Flow with infinitesimal initialization converges to the solution that minimizes th
Externí odkaz:
http://arxiv.org/abs/2012.09839
A common strategy in modern learning systems is to learn a representation that is useful for many tasks, a.k.a. representation learning. We study this strategy in the imitation learning setting for Markov decision processes (MDPs) where multiple expe
Externí odkaz:
http://arxiv.org/abs/2002.10544