Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Geng, Zijie"'
Autor:
Liu, Haoyang, Wang, Jie, Zhang, Wanbo, Geng, Zijie, Kuang, Yufei, Li, Xijun, Li, Bin, Zhang, Yongdong, Wu, Feng
Mixed-integer linear programming (MILP) is one of the most popular mathematical formulations with numerous applications. In practice, improving the performance of MILP solvers often requires a large amount of high-quality data, which can be challengi
Externí odkaz:
http://arxiv.org/abs/2410.22806
Autor:
Wang, Zhihai, Geng, Zijie, Tu, Zhaojie, Wang, Jie, Qian, Yuxi, Xu, Zhexuan, Liu, Ziyan, Xu, Siyuan, Tang, Zhentao, Kai, Shixiong, Yuan, Mingxuan, Hao, Jianye, Li, Bin, Zhang, Yongdong, Wu, Feng
The increasing complexity of modern very-large-scale integration (VLSI) design highlights the significance of Electronic Design Automation (EDA) technologies. Chip placement is a critical step in the EDA workflow, which positions chip modules on the
Externí odkaz:
http://arxiv.org/abs/2407.15026
Learning neural operators for solving partial differential equations (PDEs) has attracted great attention due to its high inference efficiency. However, training such operators requires generating a substantial amount of labeled data, i.e., PDE probl
Externí odkaz:
http://arxiv.org/abs/2401.09516
Autor:
Li, Xijun, Zhu, Fangzhou, Zhen, Hui-Ling, Luo, Weilin, Lu, Meng, Huang, Yimin, Fan, Zhenan, Zhou, Zirui, Kuang, Yufei, Wang, Zhihai, Geng, Zijie, Li, Yang, Liu, Haoyang, An, Zhiwu, Yang, Muming, Li, Jianshu, Wang, Jie, Yan, Junchi, Sun, Defeng, Zhong, Tao, Zhang, Yong, Zeng, Jia, Yuan, Mingxuan, Hao, Jianye, Yao, Jun, Mao, Kun
In an era of digital ubiquity, efficient resource management and decision-making are paramount across numerous industries. To this end, we present a comprehensive study on the integration of machine learning (ML) techniques into Huawei Cloud's OptVer
Externí odkaz:
http://arxiv.org/abs/2401.05960
In the past few years, there has been an explosive surge in the use of machine learning (ML) techniques to address combinatorial optimization (CO) problems, especially mixed-integer linear programs (MILPs). Despite the achievements, the limited avail
Externí odkaz:
http://arxiv.org/abs/2310.02807
Autor:
Wang, Jie, Yang, Rui, Geng, Zijie, Shi, Zhihao, Ye, Mingxuan, Zhou, Qi, Ji, Shuiwang, Li, Bin, Zhang, Yongdong, Wu, Feng
Generalization in partially observed markov decision processes (POMDPs) is critical for successful applications of visual reinforcement learning (VRL) in real scenarios. A widely used idea is to learn task-relevant representations that encode task-re
Externí odkaz:
http://arxiv.org/abs/2302.09601
Autor:
Geng, Zijie, Xie, Shufang, Xia, Yingce, Wu, Lijun, Qin, Tao, Wang, Jie, Zhang, Yongdong, Wu, Feng, Liu, Tie-Yan
De novo molecular generation is an essential task for science discovery. Recently, fragment-based deep generative models have attracted much research attention due to their flexibility in generating novel molecules based on existing molecule fragment
Externí odkaz:
http://arxiv.org/abs/2302.01129
Generalization across different environments with the same tasks is critical for successful applications of visual reinforcement learning (RL) in real scenarios. However, visual distractions -- which are common in real scenes -- from high-dimensional
Externí odkaz:
http://arxiv.org/abs/2205.10218
Publikováno v:
In Journal of Energy Storage 1 April 2024 83
Autor:
Pi, Zheshun, Liu, Weici, Song, Chenghu, Zhu, Chuandong, Liu, Jiwei, Wang, Lu, He, Zhao, Yang, Chengliang, Wu, Lei, Liu, Tianshuo, Geng, Zijie, Tebbutt, Scott J., Liu, Ningning, Wan, Yuan, Zhang, Faming, Mao, Wenjun
Publikováno v:
iMeta; Oct2024, Vol. 3 Issue 5, p1-7, 7p