68 citations · 230 across the 38 of their papers we have counts for
11 papers · 1 filter
TSSRGCN: Temporal Spectral Spatial Retrieval Graph Convolutional Network for Traffic Flow Forecasting
Xu Chen, Yuanxing Zhang, Lun Du +4
Traffic flow forecasting is of great significance for improving the efficiency of transportation systems and preventing emergencies. Due to the highly non-linearity and intricate e…
MetaSensing: Intelligent Metasurface Assisted RF 3D Sensing by Deep Reinforcement Learning
Jingzhi Hu, Hongliang Zhang, Kaigui Bian +3
Using RF signals for wireless sensing has gained increasing attention. However, due to the unwanted multi-path fading in uncontrollable radio environments, the accuracy of RF sensi…
MetaLocalization: Reconfigurable Intelligent Surface Aided Multi-user Wireless Indoor Localization
Haobo Zhang, Hongliang Zhang, Boya Di +3
The received signal strength (RSS) based technique is extensively utilized for localization in the indoor environments. Since the RSS values of neighboring locations may be similar…
Differentiable Feature Aggregation Search for Knowledge Distillation
Yushuo Guan, Pengyu Zhao, Bingxuan Wang +4
Knowledge distillation has become increasingly important in model compression. It boosts the performance of a miniaturized student network with the supervision of the output distri…
MetaRadar: Indoor Localization by Reconfigurable Metamaterials
Haobo Zhang, Jingzhi Hu, Hongliang Zhang +4
Indoor localization has drawn much attention owing to its potential for supporting location based services. Among various indoor localization techniques, the received signal streng…
Towards Ubiquitous Positioning by Leveraging Reconfigurable Intelligent Surface
Haobo Zhang, Hongliang Zhang, Boya Di +3
The received signal strength (RSS) based technique is widely utilized for ubiquitous positioning due to its advantage of simple implementability. However, its accuracy is limited b…
Characterizing Impacts of Heterogeneity in Federated Learning upon Large-Scale Smartphone Data
Chengxu Yang, Qipeng Wang, Mengwei Xu +4
Federated learning (FL) is an emerging, privacy-preserving machine learning paradigm, drawing tremendous attention in both academia and industry. A unique characteristic of FL is h…
AMEIR: Automatic Behavior Modeling, Interaction Exploration and MLP Investigation in the Recommender System
Pengyu Zhao, Kecheng Xiao, Yuanxing Zhang +2
Recently, deep learning models have been widely spread in the industrial recommender systems and boosted the recommendation quality. Though having achieved remarkable success, the…
A New Perspective for Flexible Feature Gathering in Scene Text Recognition Via Character Anchor Pooling
Shangbang Long, Yushuo Guan, Kaigui Bian +1
Irregular scene text recognition has attracted much attention from the research community, mainly due to the complexity of shapes of text in natural scene. However, recent methods…
Transfer Heterogeneous Knowledge Among Peer-to-Peer Teammates: A Model Distillation Approach
Zeyue Xue, Shuang Luo, Chao Wu +3
Peer-to-peer knowledge transfer in distributed environments has emerged as a promising method since it could accelerate learning and improve team-wide performance without relying o…
Federated Neural Architecture Search
Jinliang Yuan, Mengwei Xu, Yuxin Zhao +4
To preserve user privacy while enabling mobile intelligence, techniques have been proposed to train deep neural networks on decentralized data. However, training over decentralized…