20 citations · 59 across the 11 of their papers we have counts for
14 papers
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…
Cycle-Balanced Representation Learning For Counterfactual Inference
Guanglin Zhou, Lina Yao, Xiwei Xu +2
With the widespread accumulation of observational data, researchers obtain a new direction to learn counterfactual effects in many domains (e.g., health care and computational adve…
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…
AskMe: Joint Individual-level and Community-level Behavior Interaction for Question Recommendation
Nuo Li, Bin Guo, Yan Liu +3
Questions in Community Question Answering (CQA) sites are recommended to users, mainly based on users' interest extracted from questions that users have answered or have asked. How…
Unsupervised Person Re-Identification: A Systematic Survey of Challenges and Solutions
Xiangtan Lin, Pengzhen Ren, Chung-Hsing Yeh +3
Person re-identification (Re-ID) has been a significant research topic in the past decade due to its real-world applications and research significance. While supervised person Re-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…