no code implementations • 19 Apr 2024 • Peng Liu, Cong Xu, Ming Zhao, Jiawei Zhu, Bin Wang, Yi Ren
Recently, to optimize long-term user satisfaction within a recommendation session, Reinforcement Learning (RL) is used for MTF in the industry.
no code implementations • 8 Nov 2023 • Tao Chen, Shilian Zheng, Jiawei Zhu, Qi Xuan, Xiaoniu Yang
In wireless communication systems, the asynchronization of the oscillators in the transmitter and the receiver along with the Doppler shift due to relative movement may lead to the presence of carrier frequency offset (CFO) in the received signals.
no code implementations • 8 Dec 2022 • Jiawei Zhu, Mei Hong, Ronghua Du, Haifeng Li
Then we compute the structural equivalence of node pairs based on their topological features.
1 code implementation • 15 Oct 2022 • Haifeng Li, Jun Cao, Jiawei Zhu, Qinyao Luo, Silu He, Xuyin Wang
iGCL designs the invariant-discriminative loss (ID loss) to learn invariant and discriminative representations.
1 code implementation • 10 Oct 2022 • Yunlei Liang, Jiawei Zhu, Wen Ye, Song Gao
Community Detection algorithms are used to detect densely connected components in complex networks and reveal underlying relationships among components.
no code implementations • 30 Jun 2021 • Haifeng Li, Jun Cao, Jiawei Zhu, Yu Liu, Qing Zhu, Guohua Wu
And we propose Curvature Graph Neural Network (CGNN), which effectively improves the adaptive locality ability of GNNs by leveraging the structural property of graph curvature.
no code implementations • 2 Mar 2021 • Haifeng Li, Jun Cao, Jiawei Zhu, Qing Zhu, Guohua Wu
A class of GNNs solves this problem by learning implicit weights to represent the importance of neighbor nodes, which we call implicit GNNs such as Graph Attention Network.
1 code implementation • 26 Nov 2020 • Jiawei Zhu, Xin Han, Hanhan Deng, Chao Tao, Ling Zhao, Pu Wang, Lin Tao, Haifeng Li
On this background, this study presents a knowledge representation-driven traffic forecasting method based on spatial-temporal graph convolutional networks.
no code implementations • 22 Nov 2020 • Jiawei Zhu, Chao Tao, Hanhan Deng, Ling Zhao, Pu Wang, Tao Lin, Haifeng Li
Traffic forecasting is a fundamental and challenging task in the field of intelligent transportation.
no code implementations • 28 Sep 2020 • Haifeng Li, Zhenqi Cui, Zhiqing Zhu, Li Chen, Jiawei Zhu, Haozhe Huang, Chao Tao
On the one hand, RS-MetaNet raises the level of learning from the sample to the task by organizing training in a meta way, and it learns to learn a metric space that can well classify remote sensing scenes from a series of tasks.
2 code implementations • 20 Jun 2020 • Jiawei Zhu, Yujiao Song, Ling Zhao, Haifeng Li
In this study, an attention temporal graph convolutional network (A3T-GCN) traffic forecasting method was proposed to simultaneously capture global temporal dynamics and spatial correlations.
2 code implementations • 7 Mar 2020 • Jie Chen, Ziyang Yuan, Jian Peng, Li Chen, Haozhe Huang, Jiawei Zhu, Yu Liu, Haifeng Li
However, the available methods focus mainly on the difference information between multitemporal remote sensing images and lack robustness to pseudo-change information.
no code implementations • 27 Jan 2020 • Jie Chen, Haozhe Huang, Jian Peng, Jiawei Zhu, Li Chen, Wenbo Li, Binyu Sun, Haifeng Li
The feature-learning procedure of CNN largely depends on the architecture of CNN.
2 code implementations • 22 Oct 2018 • Enqiang Guo, Xinsha Fu, Jiawei Zhu, Min Deng, Yu Liu, Qing Zhu, Haifeng Li
A critical challenge problem of scene change detection is that noisy changes generated by varying illumination, shadows and camera viewpoint make variances of a scene difficult to define and measure since the noisy changes and semantic ones are entangled.