123 citations · 194 across the 3 of their papers we have counts for
5 papers
One for All, All for One: Learning and Transferring User Embeddings for Cross-Domain Recommendation
Chenglin Li, Yuanzhen Xie, Chenyun Yu +5
Cross-domain recommendation is an important method to improve recommender system performance, especially when observations in target domains are sparse. However, most existing tech…
Similarity Embedding Networks for Robust Human Activity Recognition
Chenglin Li, Carrie Lu Tong, Di Niu +5
Deep learning models for human activity recognition (HAR) based on sensor data have been heavily studied recently. However, the generalization ability of deep models on complex rea…
Meta-HAR: Federated Representation Learning for Human Activity Recognition
Chenglin Li, Di Niu, Bei Jiang +2
Human activity recognition (HAR) based on mobile sensors plays an important role in ubiquitous computing. However, the rise of data regulatory constraints precludes collecting priv…
Android Malware Detection using Large-scale Network Representation Learning
Rui Zhu, Chenglin Li, Di Niu +2
With the growth of mobile devices and applications, the number of malicious software, or malware, is rapidly increasing in recent years, which calls for the development of advanced…
Android Malware Detection based on Factorization Machine
Chenglin Li, Keith Mills, Rui Zhu +3
As the popularity of Android smart phones has increased in recent years, so too has the number of malicious applications. Due to the potential for data theft mobile phone users fac…