1.5k citations · 5.2k across the 61 of their papers we have counts for
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Generative Inverse Deep Reinforcement Learning for Online Recommendation
Xiaocong Chen, Lina Yao, Aixin Sun +3
Deep reinforcement learning enables an agent to capture user's interest through interactions with the environment dynamically. It has attracted great interest in the recommendation…
Knowledge Adaption for Demand Prediction based on Multi-task Memory Neural Network
Can Li, Lei Bai, Wei Liu +2
Accurate demand forecasting of different public transport modes(e.g., buses and light rails) is essential for public service operation.However, the development level of various mod…
TRec: Sequential Recommender Based On Latent Item Trend Information
Ye Tao, Can Wang, Lina Yao +2
Recommendation system plays an important role in online web applications. Sequential recommender further models user short-term preference through exploiting information from lates…
Face to Purchase: Predicting Consumer Choices with Structured Facial and Behavioral Traits Embedding
Zhe Liu, Xianzhi Wang, Lina Yao +3
Predicting consumers' purchasing behaviors is critical for targeted advertisement and sales promotion in e-commerce. Human faces are an invaluable source of information for gaining…
Spectrum-Guided Adversarial Disparity Learning
Zhe Liu, Lina Yao, Lei Bai +2
It has been a significant challenge to portray intraclass disparity precisely in the area of activity recognition, as it requires a robust representation of the correlation between…
Recommender Systems for the Internet of Things: A Survey
May Altulyan, Lina Yao, Xianzhi Wang +3
Recommendation represents a vital stage in developing and promoting the benefits of the Internet of Things (IoT). Traditional recommender systems fail to exploit ever-growing, dyna…
MAMO: Memory-Augmented Meta-Optimization for Cold-start Recommendation
Manqing Dong, Feng Yuan, Lina Yao +2
A common challenge for most current recommender systems is the cold-start problem. Due to the lack of user-item interactions, the fine-tuned recommender systems are unable to handl…
Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting
Lei Bai, Lina Yao, Can Li +2
Modeling complex spatial and temporal correlations in the correlated time series data is indispensable for understanding the traffic dynamics and predicting the future status of an…
NP-PROV: Neural Processes with Position-Relevant-Only Variances
Xuesong Wang, Lina Yao, Xianzhi Wang +1
Neural Processes (NPs) families encode distributions over functions to a latent representation, given context data, and decode posterior mean and variance at unknown locations. Sin…
Adversarial Attacks and Detection on Reinforcement Learning-Based Interactive Recommender Systems
Yuanjiang Cao, Xiaocong Chen, Lina Yao +2
Adversarial attacks pose significant challenges for detecting adversarial attacks at an early stage. We propose attack-agnostic detection on reinforcement learning-based interactiv…
Agglomerative Neural Networks for Multi-view Clustering
Zhe Liu, Yun Li, Lina Yao +2
Conventional multi-view clustering methods seek for a view consensus through minimizing the pairwise discrepancy between the consensus and subviews. However, the pairwise compariso…
Are You A Risk Taker? Adversarial Learning of Asymmetric Cross-Domain Alignment for Risk Tolerance Prediction
Zhe Liu, Lina Yao, Xianzhi Wang +2
Most current studies on survey analysis and risk tolerance modelling lack professional knowledge and domain-specific models. Given the effectiveness of generative adversarial learn…
Knowledge-guided Deep Reinforcement Learning for Interactive Recommendation
Xiaocong Chen, Chaoran Huang, Lina Yao +3
Interactive recommendation aims to learn from dynamic interactions between items and users to achieve responsiveness and accuracy. Reinforcement learning is inherently advantageous…
Survey for Trust-aware Recommender Systems: A Deep Learning Perspective
Manqing Dong, Feng Yuan, Lina Yao +3
A significant remaining challenge for existing recommender systems is that users may not trust the recommender systems for either lack of explanation or inaccurate recommendation r…
A Multi-view CNN-based Acoustic Classification System for Automatic Animal Species Identification
Weitao Xu, Xiang Zhang, Lina Yao +2
Automatic identification of animal species by their vocalization is an important and challenging task. Although many kinds of audio monitoring system have been proposed in the lite…
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
Kaixuan Chen, Dalin Zhang, Lina Yao +3
The vast proliferation of sensor devices and Internet of Things enables the applications of sensor-based activity recognition. However, there exist substantial challenges that coul…