943 citations · 1.2k across the 22 of their papers we have counts for
6 papers · 1 filter
A Framework of Transferring Structures Across Large-scale Information Networks
Shan Xue, Jie Lu, Guangquan Zhang +1
The existing domain-specific methods for mining information networks in machine learning aims to represent the nodes of an information network into a vector format. However, the re…
ATL: Autonomous Knowledge Transfer from Many Streaming Processes
Mahardhika Pratama, Marcus de Carvalho, Renchunzi Xie +2
Transferring knowledge across many streaming processes remains an uncharted territory in the existing literature and features unique characteristics: no labelled instance of the ta…
Cross-domain Network Representations
Shan Xue, Jie Lu, Guangquan Zhang
The purpose of network representation is to learn a set of latent features by obtaining community information from network structures to provide knowledge for machine learning task…
Open Set Domain Adaptation: Theoretical Bound and Algorithm
Zhen Fang, Jie Lu, Feng Liu +2
The aim of unsupervised domain adaptation is to leverage the knowledge in a labeled (source) domain to improve a model's learning performance with an unlabeled (target) domain -- t…
Butterfly: One-step Approach towards Wildly Unsupervised Domain Adaptation
Feng Liu, Jie Lu, Bo Han +3
In unsupervised domain adaptation (UDA), classifiers for the target domain (TD) are trained with clean labeled data from the source domain (SD) and unlabeled data from TD. However,…
A Choquet Fuzzy Integral Vertical Bagging Classifier for Mobile Telematics Data Analysis
Mohammad Siami, Mohsen Naderpour, Jie Lu
Mobile app development in recent years has resulted in new products and features to improve human life. Mobile telematics is one such development that encompasses multidisciplinary…