Zobrazeno 1 - 10
of 108
pro vyhledávání: '"Ye, Yuyang"'
With the shrinking technology nodes, timing optimization becomes increasingly challenging. Approximate logic synthesis (ALS) can perform local approximate changes (LACs) on circuits to optimize timing with the cost of slight inaccuracy. However, exis
Externí odkaz:
http://arxiv.org/abs/2411.10990
In this paper, we study the Cauchy problem for backward stochastic partial differential equations (BSPDEs) involving fractional Laplacian operator. Firstly, by employing the martingale representation theorem and the fractional heat kernel, we constru
Externí odkaz:
http://arxiv.org/abs/2409.07052
Autor:
Ye, Yuyang, Zheng, Zhi, Shen, Yishan, Wang, Tianshu, Zhang, Hengruo, Zhu, Peijun, Yu, Runlong, Zhang, Kai, Xiong, Hui
Recent advances in Large Language Models (LLMs) have demonstrated significant potential in the field of Recommendation Systems (RSs). Most existing studies have focused on converting user behavior logs into textual prompts and leveraging techniques s
Externí odkaz:
http://arxiv.org/abs/2408.09698
Autor:
Ye, Yuyang, Tang, Lu-An, Wang, Haoyu, Yu, Runlong, Yu, Wenchao, He, Erhu, Chen, Haifeng, Xiong, Hui
Achieving carbon neutrality within industrial operations has become increasingly imperative for sustainable development. It is both a significant challenge and a key opportunity for operational optimization in industry 4.0. In recent years, Deep Rein
Externí odkaz:
http://arxiv.org/abs/2407.08910
Autor:
Gao, Jingtong, Chen, Bo, Zhao, Xiangyu, Liu, Weiwen, Li, Xiangyang, Wang, Yichao, Zhang, Zijian, Wang, Wanyu, Ye, Yuyang, Lin, Shanru, Guo, Huifeng, Tang, Ruiming
Reranking is a critical component in recommender systems, playing an essential role in refining the output of recommendation algorithms. Traditional reranking models have focused predominantly on accuracy, but modern applications demand consideration
Externí odkaz:
http://arxiv.org/abs/2406.12433
In this paper, we construct a type of interacting particle systems to approximate a class of stochastic different equations whose coefficients depend on the conditional probability distributions of the processes given partial observations. After prov
Externí odkaz:
http://arxiv.org/abs/2403.17555
Gate sizing plays an important role in timing optimization after physical design. Existing machine learning-based gate sizing works cannot optimize timing on multiple timing paths simultaneously and neglect the physical constraint on layouts. They ca
Externí odkaz:
http://arxiv.org/abs/2403.08193
Autor:
Xu, Derong, Zhang, Ziheng, Zhu, Zhihong, Lin, Zhenxi, Liu, Qidong, Wu, Xian, Xu, Tong, Wang, Wanyu, Ye, Yuyang, Zhao, Xiangyu, Chen, Enhong, Zheng, Yefeng
Model editing aims to precisely alter the behaviors of large language models (LLMs) in relation to specific knowledge, while leaving unrelated knowledge intact. This approach has proven effective in addressing issues of hallucination and outdated inf
Externí odkaz:
http://arxiv.org/abs/2402.18099
Autor:
Bai, Xianyong, Tian, Hui, Deng, Yuanyong, Wang, Zhanshan, Yang, Jianfeng, Zhang, Xiaofeng, Zhang, Yonghe, Qi, Runze, Wang, Nange, Gao, Yang, Yu, Jun, He, Chunling, Shen, Zhengxiang, Shen, Lun, Guo, Song, Hou, Zhenyong, Ji, Kaifan, Bi, Xingzi, Duan, Wei, Yang, Xiao, Lin, Jiaben, Hu, Ziyao, Song, Qian, Yang, Zihao, Chen, Yajie, Qiao, Weidong, Ge, Wei, Li, Fu, Jin, Lei, He, Jiawei, Chen, Xiaobo, Zhu, Xiaocheng, He, Junwang, Shi, Qi, Liu, Liu, Li, Jinsong, Xu, Dongxiao, Liu, Rui, Li, Taijie, Feng, Zhenggong, Wang, Yamin, Fan, Chengcheng, Liu, Shuo, Guo, Sifan, Sun, Zheng, Wu, Yuchuan, Li, Haiyu, Yang, Qi, Ye, Yuyang, Gu, Weichen, Wu, Jiali, Zhang, Zhe, Yu, Yue, Ye, Zeyi, Sheng, Pengfeng, Wang, Yifan, Li, Wenbin, Huang, Qiushi, Zhang, Zhong
The Solar Upper Transition Region Imager (SUTRI) onboard the Space Advanced Technology demonstration satellite (SATech-01), which was launched to a sun-synchronous orbit at a height of 500 km in July 2022, aims to test the on-orbit performance of our
Externí odkaz:
http://arxiv.org/abs/2303.03669
Autor:
Ye, Yuyang, Liu, Gengyuan, Agostinho, Feni, Almeida, Cecilia M.V.B., Giannetti, Biagio F., Ulgiati, Sergio, Li, Hui
Publikováno v:
In Sustainable Energy Technologies and Assessments December 2024 72
