Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Hua, Zhigang"'
Autor:
Sancak, Kaan, Hua, Zhigang, Fang, Jin, Xie, Yan, Malevich, Andrey, Long, Bo, Balin, Muhammed Fatih, Çatalyürek, Ümit V.
Graph Neural Networks (GNNs) have shown impressive performance in graph representation learning, but they face challenges in capturing long-range dependencies due to their limited expressive power. To address this, Graph Transformers (GTs) were intro
Externí odkaz:
http://arxiv.org/abs/2406.12059
Autor:
Fu, Dongqi, Hua, Zhigang, Xie, Yan, Fang, Jin, Zhang, Si, Sancak, Kaan, Wu, Hao, Malevich, Andrey, He, Jingrui, Long, Bo
Graph transformer has been proven as an effective graph learning method for its adoption of attention mechanism that is capable of capturing expressive representations from complex topological and feature information of graphs. Graph transformer conv
Externí odkaz:
http://arxiv.org/abs/2403.16030
Autor:
Zhou, Jun, Qi, Feng, Hua, Zhigang, Jian, Daohong, Liu, Ziqi, Wu, Hua, Zhang, Xingwen, Yang, Shuang
Assigning items to owners is a common problem found in various real-world applications, for example, audience-channel matching in marketing campaigns, borrower-lender matching in loan management, and shopper-merchant matching in e-commerce. Given an
Externí odkaz:
http://arxiv.org/abs/2210.16986
Publikováno v:
In Sustainable Cities and Society 1 October 2024 112
Autor:
Wang, Runzhong, Hua, Zhigang, Liu, Gan, Zhang, Jiayi, Yan, Junchi, Qi, Feng, Yang, Shuang, Zhou, Jun, Yang, Xiaokang
Combinatorial Optimization (CO) has been a long-standing challenging research topic featured by its NP-hard nature. Traditionally such problems are approximately solved with heuristic algorithms which are usually fast but may sacrifice the solution q
Externí odkaz:
http://arxiv.org/abs/2106.04927
Scheduling computational tasks represented by directed acyclic graphs (DAGs) is challenging because of its complexity. Conventional scheduling algorithms rely heavily on simple heuristics such as shortest job first (SJF) and critical path (CP), and a
Externí odkaz:
http://arxiv.org/abs/2103.03412
We examine the \emph{submodular maximum coverage problem} (SMCP), which is related to a wide range of applications. We provide the first variational approximation for this problem based on the Nemhauser divergence, and show that it can be solved effi
Externí odkaz:
http://arxiv.org/abs/2006.05583
Knapsack problems (KPs) are common in industry, but solving KPs is known to be NP-hard and has been tractable only at a relatively small scale. This paper examines KPs in a slightly generalized form and shows that they can be solved nearly optimally
Externí odkaz:
http://arxiv.org/abs/2002.00352
Autor:
Hu Guangyu, Hua Zhigang
Publikováno v:
Journal of Computational and Theoretical Nanoscience. 13:10412-10416
Publikováno v:
The Open Petroleum Engineering Journal. 8:138-141
A method of global optimizing power generation is introduced in this paper. Under the condition of maintaining the same working hours of different units, electricity quantity generated between the different power suppliers is equal in one province, a