2 citations · 3 across the 5 of their papers we have counts for
5 papers
Optimizing Feature Extraction for On-device Model Inference with User Behavior Sequences
Chen Gong, Zhenzhe Zheng, Yiliu Chen +3
Machine learning models are widely integrated into modern mobile apps to analyze user behaviors and deliver personalized services. Ensuring low-latency on-device model execution is…
Optimizing Storage Overhead of User Behavior Log for ML-embedded Mobile Apps
Chen Gong, Yan Zhuang, Zhenzhe Zheng +4
Machine learning (ML) models are increasingly integrated into modern mobile apps to enable personalized and intelligent services. These models typically rely on rich input features…
A Two-Stage Data Selection Framework for Data-Efficient Model Training on Edge Devices
Chen Gong, Rui Xing, Zhenzhe Zheng +1
The demand for machine learning (ML) model training on edge devices is escalating due to data privacy and personalized service needs. However, we observe that current on-device mod…
Delta: A Cloud-assisted Data Enrichment Framework for On-Device Continual Learning
Chen Gong, Zhenzhe Zheng, Fan Wu +2
In modern mobile applications, users frequently encounter various new contexts, necessitating on-device continual learning (CL) to ensure consistent model performance. While existi…
To Store or Not? Online Data Selection for Federated Learning with Limited Storage
Chen Gong, Zhenzhe Zheng, Yunfeng Shao +3
Machine learning models have been deployed in mobile networks to deal with massive data from different layers to enable automated network management and intelligence on devices. To…