319 citations · 333 across the 6 of their papers we have counts for
6 papers
Design Automation for Fast, Lightweight, and Effective Deep Learning Models: A Survey
Dalin Zhang, Kaixuan Chen, Yan Zhao +3
Deep learning technologies have demonstrated remarkable effectiveness in a wide range of tasks, and deep learning holds the potential to advance a multitude of applications, includ…
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
Kaixuan Chen, Dalin Zhang, Lina Yao +3
The vast proliferation of sensor devices and Internet of Things enables the applications of sensor-based activity recognition. However, there exist substantial challenges that coul…
Multi-agent Attentional Activity Recognition
Kaixuan Chen, Lina Yao, Dalin Zhang +2
Multi-modality is an important feature of sensor based activity recognition. In this work, we consider two inherent characteristics of human activities, the spatially-temporally va…
Distributionally Robust Semi-Supervised Learning for People-Centric Sensing
Kaixuan Chen, Lina Yao, Dalin Zhang +3
Semi-supervised learning is crucial for alleviating labelling burdens in people-centric sensing. However, human-generated data inherently suffer from distribution shift in semi-sup…
Interpretable Parallel Recurrent Neural Networks with Convolutional Attentions for Multi-Modality Activity Modeling
Kaixuan Chen, Lina Yao, Xianzhi Wang +4
Multimodal features play a key role in wearable sensor-based human activity recognition (HAR). Selecting the most salient features adaptively is a promising way to maximize the eff…
Fullie and Wiselie: A Dual-Stream Recurrent Convolutional Attention Model for Activity Recognition
Kaixuan Chen, Lina Yao, Tao Gu +3
Multimodal features play a key role in wearable sensor based Human Activity Recognition (HAR). Selecting the most salient features adaptively is a promising way to maximize the eff…