no code implementations • 19 Mar 2024 • Heng Wang, Jianhua Zhang, Gaofeng Nie, Li Yu, Zhiqiang Yuan, Tongjie Li, Jialin Wang, Guangyi Liu
Digital twin channel (DTC) is the real-time mapping of a wireless channel from the physical world to the digital world, which is expected to provide significant performance enhancements for the sixth-generation (6G) air-interface design.
no code implementations • 5 Feb 2024 • Hao Zhu, Kefan Jin, Rui Gao, Jialin Wang, C. -J. Richard Shi
Existing trajectory planning methods are struggling to handle the issue of autonomous track swinging during navigation, resulting in significant errors when reaching the destination.
no code implementations • 16 Dec 2023 • Jialin Wang, Jianhua Zhang, Yuxiang Zhang, Yutong Sun, Gaofeng, Nie, Lianzheng Shi, Ping Zhang, Guangyi Liu
The digital twin channel (DTC) is crucial for 6G wireless autonomous networks as it replicates the wireless channel fading states in 6G air interface transmissions.
no code implementations • 24 Mar 2022 • Jialin Wang, Rui Gao, Haotian Zheng, Hao Zhu, C. -J. Richard Shi
Compared with the existing literature, our WNFG of EEG signals achieves up to 10 times of redundant edge reduction, and our approach achieves up to 97 times of model pruning without loss of classification accuracy.
no code implementations • 9 May 2019 • Di Zhao, Jiqiang Liu, Jialin Wang, Wenjia Niu, Endong Tong, Tong Chen, Gang Li
"Feint Attack" is simulated by the real attack inserted in the normal causal attack chain, and the addition of the real attack destroys the causal relationship of the original attack chain.
no code implementations • 19 Nov 2018 • Chenchen Li, Jialin Wang, Hongwei Wang, Miao Zhao, Wenjie Li, Xiaotie Deng
To enhance the emotion discriminativeness of words in textual feature extraction, we propose Emotional Word Embedding (EWE) to learn text representations by jointly considering their semantics and emotions.
9 code implementations • 9 Mar 2018 • Hongwei Wang, Fuzheng Zhang, Jialin Wang, Miao Zhao, Wenjie Li, Xing Xie, Minyi Guo
To address the sparsity and cold start problem of collaborative filtering, researchers usually make use of side information, such as social networks or item attributes, to improve recommendation performance.
Ranked #2 on Click-Through Rate Prediction on Book-Crossing
5 code implementations • 22 Nov 2017 • Hongwei Wang, Jia Wang, Jialin Wang, Miao Zhao, Wei-Nan Zhang, Fuzheng Zhang, Xing Xie, Minyi Guo
The goal of graph representation learning is to embed each vertex in a graph into a low-dimensional vector space.
Ranked #1 on Node Classification on Wikipedia