81 citations · 358 across the 18 of their papers we have counts for
7 papers · 1 filter
Software Expert Discovery via Knowledge Domain Embeddings in a Collaborative Network
Chaoran Huang, Lina Yao, Xianzhi Wang +2
Community Question Answering (CQA) websites can be claimed as the most major venues for knowledge sharing, and the most effective way of exchanging knowledge at present. Considerin…
Brain2Object: Printing Your Mind from Brain Signals with Spatial Correlation Embedding
Xiang Zhang, Lina Yao, Chaoran Huang +3
Electroencephalography (EEG) signals are known to manifest differential patterns when individuals visually concentrate on different objects. In this work, we present an end-to-end…
Internet of Things Meets Brain-Computer Interface: A Unified Deep Learning Framework for Enabling Human-Thing Cognitive Interactivity
Xiang Zhang, Lina Yao, Shuai Zhang +3
A Brain-Computer Interface (BCI) acquires brain signals, analyzes and translates them into commands that are relayed to actuation devices for carrying out desired actions. With the…
Multi-modality Sensor Data Classification with Selective Attention
Xiang Zhang, Lina Yao, Chaoran Huang +4
Multimodal wearable sensor data classification plays an important role in ubiquitous computing and has a wide range of applications in scenarios from healthcare to entertainment. H…
Context-aware Human Intent Inference for Improving Human Machine Cooperation
Xiang Zhang
The ability of human beings to precisely recog- nize others intents is a significant mental activity in reasoning about actions, such as, what other people are doing and what they…
Metric Factorization: Recommendation beyond Matrix Factorization
Shuai Zhang, Lina Yao, Yi Tay +3
In the past decade, matrix factorization has been extensively researched and has become one of the most popular techniques for personalized recommendations. Nevertheless, the dot p…
Know Your Mind: Adaptive Brain Signal Classification with Reinforced Attentive Convolutional Neural Networks
Xiang Zhang, Lina Yao, Xianzhi Wang +3
Electroencephalography (EEG) signals reflect activities on certain brain areas. Effective classification of time-varying EEG signals is still challenging. First, EEG signal process…