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Wei Zhang
Researcher at East China Normal University
Publications - 130
Citations - 2205
Wei Zhang is an academic researcher from East China Normal University. The author has contributed to research in topics: Computer science & Graph (abstract data type). The author has an hindex of 18, co-authored 91 publications receiving 1286 citations. Previous affiliations of Wei Zhang include Shanghai Jiao Tong University & Tsinghua University.
Papers
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Proceedings ArticleDOI
Combining latent factor model with location features for event-based group recommendation
Wei Zhang,Jianyong Wang,Wei Feng +2 more
TL;DR: A method called Pairwise Tag enhAnced and featuRe-based Matrix factorIzation for Group recommendAtioN (PTARMIGAN), which considers location features, social features, and implicit patterns simultaneously in a unified model to provide better group recommendations.
Proceedings ArticleDOI
STREAMCUBE: Hierarchical spatio-temporal hashtag clustering for event exploration over the Twitter stream
TL;DR: This paper focuses on hierarchical spatio-temporal hashtag clustering techniques and proposes a data structure called STREAMCUBE, which is an extension of the data cube structure from the database community with spatial and temporal hierarchy.
Proceedings ArticleDOI
Source-Free Domain Adaptation for Semantic Segmentation
Yuang Liu,Wei Zhang,Jun Wang +2 more
TL;DR: Zhang et al. as mentioned in this paper proposed a source-free domain adaptation framework for semantic segmentation, in which only a well-trained source model and an unlabeled target domain dataset are available for adaptation, which not only enables recovering and preserving the source domain knowledge from the source model via knowledge transfer during model adaptation, but also distills valuable information from the target domain for self-supervised learning.
Proceedings ArticleDOI
Supervised Reinforcement Learning with Recurrent Neural Network for Dynamic Treatment Recommendation
TL;DR: Supervised Reinforcement Learning with Recurrent Neural Network (SRL-RNN) is proposed, which fuses them into a synergistic learning framework to handle complex relations among multiple medications, diseases and individual characteristics.
Proceedings ArticleDOI
A Collective Bayesian Poisson Factorization Model for Cold-start Local Event Recommendation
Wei Zhang,Jianyong Wang +1 more
TL;DR: A collective Bayesian Poisson factorization (CBPF) model is proposed for handling the new problem of cold-start local event recommendation in EBSNs and the results demonstrate the proposed model is effective and outperforms several alternative methods.