Zobrazeno 1 - 10
of 187
pro vyhledávání: '"Zhang, Rongkai"'
Large language models (LLMs) have empowered intelligent agents to execute intricate tasks within domain-specific software such as browsers and games. However, when applied to general-purpose software systems like operating systems, LLM agents face th
Externí odkaz:
http://arxiv.org/abs/2402.06596
Various distributed deep neural network (DNN) training technologies lead to increasingly complicated use of collective communications on GPU. The deadlock-prone collectives on GPU force researchers to guarantee that collectives are enqueued in a cons
Externí odkaz:
http://arxiv.org/abs/2303.06324
Autor:
Zhang, Rongkai, Zhang, Cong, Cao, Zhiguang, Song, Wen, Tan, Puay Siew, Zhang, Jie, Wen, Bihan, Dauwels, Justin
We propose a manager-worker framework based on deep reinforcement learning to tackle a hard yet nontrivial variant of Travelling Salesman Problem (TSP), \ie~multiple-vehicle TSP with time window and rejections (mTSPTWR), where customers who cannot be
Externí odkaz:
http://arxiv.org/abs/2209.06094
Image restoration schemes based on the pre-trained deep models have received great attention due to their unique flexibility for solving various inverse problems. In particular, the Plug-and-Play (PnP) framework is a popular and powerful tool that ca
Externí odkaz:
http://arxiv.org/abs/2207.12056
Autor:
Zhang, Rongkai, Amjad, Arshia, Zhang, Lujia, Zhou, Wei, Yang, Yichen, He, Qixin, Xie, Jingli, Gao, Bei
Publikováno v:
In Biochemical Engineering Journal August 2024 208
Autor:
Cai, Rulong, Jiang, Qijun, Chen, Dongli, Feng, Qi, Liang, Xinzhi, Ouyang, Zhaoming, Liao, Weijian, Zhang, Rongkai, Fang, Hang
Publikováno v:
In iScience 21 June 2024 27(6)
Low-light image enhancement (LLIE) is a pervasive yet challenging problem, since: 1) low-light measurements may vary due to different imaging conditions in practice; 2) images can be enlightened subjectively according to diverse preferences by each i
Externí odkaz:
http://arxiv.org/abs/2107.05830
State-of-the-art image denoisers exploit various types of deep neural networks via deterministic training. Alternatively, very recent works utilize deep reinforcement learning for restoring images with diverse or unknown corruptions. Though deep rein
Externí odkaz:
http://arxiv.org/abs/2107.05318
Autor:
Zheng, Hui, Fang, Jianli, Lu, Wei, Liu, Youhui, Chen, Sixu, Huang, Guangxin, Zou, Yuming, Hu, Shu, Zheng, Yongxu, Fang, Hang, Zhang, Rongkai
Publikováno v:
In Journal of Orthopaedic Translation January 2024 44:35-46
Publikováno v:
In Brain Research Bulletin January 2024 206