103 citations · 114 across the 11 of their papers we have counts for
11 papers
MTM: A Multi-Scale Token Mixing Transformer for Irregular Multivariate Time Series Classification
Shuhan Zhong, Weipeng Zhuo, Sizhe Song +3
Irregular multivariate time series (IMTS) is characterized by the lack of synchronized observations across its different channels. In this paper, we point out that this channel-wis…
Graph-based Fingerprint Update Using Unlabelled WiFi Signals
Ka Ho Chiu, Handi Yin, Weipeng Zhuo +2
WiFi received signal strength (RSS) environment evolves over time due to movement of access points (APs), AP power adjustment, installation and removal of APs, etc. We study how to…
M-Impute: Mask-guided Representation Learning for Missing Value Imputation
Zhongyi Yu, Zhenghao Wu, Shuhan Zhong +4
Missing values are a common problem that poses significant challenges to data analysis and machine learning. This problem necessitates the development of an effective imputation me…
SDT-GNN: Streaming-based Distributed Training Framework for Graph Neural Networks
Xin Huang, Weipeng Zhuo, Minh Phu Vuong +4
Recently, distributed GNN training frameworks, such as DistDGL and PyG, have been developed to enable training GNN models on large graphs by leveraging multiple GPUs in a distribut…
A Multi-Scale Decomposition MLP-Mixer for Time Series Analysis
Shuhan Zhong, Sizhe Song, Weipeng Zhuo +3
Time series data, including univariate and multivariate ones, are characterized by unique composition and complex multi-scale temporal variations. They often require special consid…
FIS-ONE: Floor Identification System with One Label for Crowdsourced RF Signals
Weipeng Zhuo, Ka Ho Chiu, Jierun Chen +4
Floor labels of crowdsourced RF signals are crucial for many smart-city applications, such as multi-floor indoor localization, geofencing, and robot surveillance. To build a predic…
Run, Don't Walk: Chasing Higher FLOPS for Faster Neural Networks
Jierun Chen, Shiu-hong Kao, Hao He +4
To design fast neural networks, many works have been focusing on reducing the number of floating-point operations (FLOPs). We observe that such reduction in FLOPs, however, does no…
GRAFICS: Graph Embedding-based Floor Identification Using Crowdsourced RF Signals
Weipeng Zhuo, Ziqi Zhao, Ka Ho Chiu +4
We study the problem of floor identification for radiofrequency (RF) signal samples obtained in a crowdsourced manner, where the signal samples are highly heterogeneous and most sa…
Semi-supervised Learning with Network Embedding on Ambient RF Signals for Geofencing Services
Weipeng Zhuo, Ka Ho Chiu, Jierun Chen +5
In applications such as elderly care, dementia anti-wandering and pandemic control, it is important to ensure that people are within a predefined area for their safety and well-bei…
TVConv: Efficient Translation Variant Convolution for Layout-aware Visual Processing
Jierun Chen, Tianlang He, Weipeng Zhuo +3
As convolution has empowered many smart applications, dynamic convolution further equips it with the ability to adapt to diverse inputs. However, the static and dynamic convolution…
Tackling Multipath and Biased Training Data for IMU-Assisted BLE Proximity Detection
Tianlang He, Jiajie Tan, Weipeng Zhuo +2
Proximity detection is to determine whether an IoT receiver is within a certain distance from a signal transmitter. Due to its low cost and high popularity, Bluetooth low energy (B…