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Automatic Device Classification from Network Traffic Streams of Internet of Things
Lei Bai, Lina Yao, Salil S. Kanhere +2
With the widespread adoption of Internet of Things (IoT), billions of everyday objects are being connected to the Internet. Effective management of these devices to support reliabl…
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…
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…
Next Item Recommendation with Self-Attention
Shuai Zhang, Yi Tay, Lina Yao +1
In this paper, we propose a novel sequence-aware recommendation model. Our model utilizes self-attention mechanism to infer the item-item relationship from user's historical intera…
Adversarial Collaborative Auto-encoder for Top-N Recommendation
Feng Yuan, Lina Yao, Boualem Benatallah
During the past decade, model-based recommendation methods have evolved from latent factor models to neural network-based models. Most of these techniques mainly focus on improving…
Expert Recommendation via Tensor Factorization with Regularizing Hierarchical Topical Relationships
Chaoran Huang, Lina Yao, Xianzhi Wang +3
Knowledge acquisition and exchange are generally crucial yet costly for both businesses and individuals, especially when the knowledge concerns various areas. Question Answering Co…
A Survey on Expert Recommendation in Community Question Answering
Xianzhi Wang, Chaoran Huang, Lina Yao +2
Community question answering (CQA) represents the type of Web applications where people can exchange knowledge via asking and answering questions. One significant challenge of most…
GrCAN: Gradient Boost Convolutional Autoencoder with Neural Decision Forest
Manqing Dong, Lina Yao, Xianzhi Wang +2
Random forest and deep neural network are two schools of effective classification methods in machine learning. While the random forest is robust irrespective of the data domain, th…
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…
Opinion Fraud Detection via Neural Autoencoder Decision Forest
Manqing Dong, Lina Yao, Xianzhi Wang +3
Online reviews play an important role in influencing buyers' daily purchase decisions. However, fake and meaningless reviews, which cannot reflect users' genuine purchase experienc…
NeuRec: On Nonlinear Transformation for Personalized Ranking
Shuai Zhang, Lina Yao, Aixin Sun +3
Modeling user-item interaction patterns is an important task for personalized recommendations. Many recommender systems are based on the assumption that there exists a linear relat…
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…
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…
Adversarially Regularized Graph Autoencoder for Graph Embedding
Shirui Pan, Ruiqi Hu, Guodong Long +3
Graph embedding is an effective method to represent graph data in a low dimensional space for graph analytics. Most existing embedding algorithms typically focus on preserving the…
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…