36 citations · 57 across the 9 of their papers we have counts for
9 papers
Dual Contrastive Transformer for Hierarchical Preference Modeling in Sequential Recommendation
Chengkai Huang, Shoujin Wang, Xianzhi Wang +1
Sequential recommender systems (SRSs) aim to predict the subsequent items which may interest users via comprehensively modeling users' complex preference embedded in the sequence o…
Modeling Temporal Positive and Negative Excitation for Sequential Recommendation
Chengkai Huang, Shoujin Wang, Xianzhi Wang +1
Sequential recommendation aims to predict the next item which interests users via modeling their interest in items over time. Most of the existing works on sequential recommendatio…
An Entropy-guided Reinforced Partial Convolutional Network for Zero-Shot Learning
Yun Li, Zhe Liu, Lina Yao +3
Zero-Shot Learning (ZSL) aims to transfer learned knowledge from observed classes to unseen classes via semantic correlations. A promising strategy is to learn a global-local repre…
Locality-Sensitive Experience Replay for Online Recommendation
Xiaocong Chen, Lina Yao, Xianzhi Wang +1
Online recommendation requires handling rapidly changing user preferences. Deep reinforcement learning (DRL) is gaining interest as an effective means of capturing users' dynamic i…
A Survey of Deep Reinforcement Learning in Recommender Systems: A Systematic Review and Future Directions
Xiaocong Chen, Lina Yao, Julian McAuley +2
In light of the emergence of deep reinforcement learning (DRL) in recommender systems research and several fruitful results in recent years, this survey aims to provide a timely an…
Global Convolutional Neural Processes
Xuesong Wang, Lina Yao, Xianzhi Wang +2
The ability to deal with uncertainty in machine learning models has become equally, if not more, crucial to their predictive ability itself. For instance, during the pandemic, gove…
Generative Adversarial Reward Learning for Generalized Behavior Tendency Inference
Xiaocong Chen, Lina Yao, Xianzhi Wang +3
Recent advances in reinforcement learning have inspired increasing interest in learning user modeling adaptively through dynamic interactions, e.g., in reinforcement learning based…
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…