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Chaochao Chen

Chaochao Chen

Overview

Chaochao Chen is affiliated with Zhejiang University in China and specializes in the field of Computer Science, with a focus on several subfields including Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Management Science and Operations Research, and Molecular Biology. The scientist's research is notably concentrated on topics related to Recommender Systems and Techniques, Privacy-Preserving Technologies in Data, Advanced Graph Neural Networks, Stochastic Gradient Optimization Techniques, Topic Modeling, Advanced Bandit Algorithms Research, and Cryptography and Data Security.

They have published extensively in a variety of venues, including:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Knowledge and Data Engineering
  • ACM Transactions on Information Systems
  • Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence

Among recent papers, the following are highlighted:

  • "Differential Private Knowledge Transfer for Privacy-Preserving Cross-Domain Recommendation," 2022, Proceedings of the ACM Web Conference 2022
  • "ASFGNN: Automated separated-federated graph neural network," 2021, Peer-to-Peer Networking and Applications
  • "A Unified Framework for Cross-Domain and Cross-System Recommendations," 2021, IEEE Transactions on Knowledge and Data Engineering
  • "Practical Privacy Preserving POI Recommendation," 2020, ACM Transactions on Intelligent Systems and Technology
  • "Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification," 2022, Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence

Frequent co-authors include:

  • Xiaolin Zheng
  • Weiming Liu
  • Yuyuan Li
  • Jun Zhou

Chaochao Chen's work spans topics deeply embedded in privacy-preserving methods and graph neural networks, with a notable presence in cross-domain recommendation systems that address both theoretical and applied challenges in knowledge transfer and privacy. The collaboration with multiple researchers across AI and data engineering venues reflects a broad engagement with the computer science community, particularly in areas intersecting privacy and advanced neural network architectures.

Best Publications

  • Heterogeneous Graph Neural Networks for Malicious Account Detection

    Ziqi Liu;Chaochao Chen;Xinxing Yang;Jun Zhou

  • GeniePath: Graph Neural Networks with Adaptive Receptive Paths

    Ziqi Liu;Chaochao Chen;Longfei Li;Jun Zhou

  • Cross-Domain Recommendation: Challenges, Progress, and Prospects

    Feng Zhu;Yan Wang;Chaochao Chen;Jun Zhou

  • DTCDR: A Framework for Dual-Target Cross-Domain Recommendation

    Feng Zhu;Chaochao Chen;Yan Wang;Guanfeng Liu

  • A graphical and attentional framework for dual-target cross-domain recommendation

    Feng Zhu;Yan Wang;Chaochao Chen;Guanfeng Liu

  • A Deep Framework for Cross-Domain and Cross-System Recommendations.

    Feng Zhu;Yan Wang;Chaochao Chen;Guanfeng Liu

  • A hybrid approach for movie recommendation via tags and ratings

    Shouxian Wei;Xiaolin Zheng;Deren Chen;Chaochao Chen

  • Context- ware collaborative topic regression with social matrix factorization for recommender systems

    Chaochao Chen;Xiaolin Zheng;Yan Wang;Fuxing Hong

  • Towards Context-aware Social Recommendation via Individual Trust

    Jun Li;Chaochao Chen;Huiling Chen;Changfei Tong

  • When Homomorphic Encryption Marries Secret Sharing: Secure Large-Scale Sparse Logistic Regression and Applications in Risk Control

    Chaochao Chen;Jun Zhou;Li Wang;Xibin Wu

  • A Unified Framework for Cross-Domain and Cross-System Recommendations

    Feng Zhu;Yan Wang;Jun Zhou;Chaochao Chen

  • FinBrain: when finance meets AI 2.0

    Xiao-lin Zheng;Meng-ying Zhu;Qi-bing Li;Chao-chao Chen

  • ASFGNN: Automated separated-federated graph neural network

    Longfei Zheng;Jun Zhou;Chaochao Chen;Bingzhe Wu

  • Distributed Deep Forest and its Application to Automatic Detection of Cash-Out Fraud

    Ya-Lin Zhang;Jun Zhou;Wenhao Zheng;Ji Feng

  • Practical Privacy Preserving POI Recommendation

    Chaochao Chen;Jun Zhou;Bingzhe Wu;Wenjing Fang

  • Privacy Preserving Point-of-Interest Recommendation Using Decentralized Matrix Factorization

    Chaochao Chen;Ziqi Liu;Peilin Zhao;Jun Zhou

  • A Hybrid Trust-Based Recommender System for Online Communities of Practice

    Xiao-Lin Zheng;Chao-Chao Chen;Jui-Long Hung;Wu He

  • KunPeng: Parameter Server based Distributed Learning Systems and Its Applications in Alibaba and Ant Financial

    Jun Zhou;Xiaolong Li;Peilin Zhao;Chaochao Chen

  • Privacy-Preserving Graph Neural Network for Node Classification.

    Jun Zhou;Chaochao Chen;Longfei Zheng;Xiaolin Zheng

  • Distributed Deep Forest and its Application to Automatic Detection of Cash-out Fraud

    Ya-Lin Zhang;Jun Zhou;Wenhao Zheng;Ji Feng

Frequent Co-Authors

Yan Wang
Yan Wang Macquarie University
Guanfeng Liu
Guanfeng Liu Macquarie University
Peilin Zhao
Peilin Zhao Tencent (China)
Le Song
Le Song Mohamed bin Zayed University of Artificial Intelligence
Alex X. Liu
Alex X. Liu Michigan State University
Guangyu Sun
Guangyu Sun Peking University
Jia Wu
Jia Wu Macquarie University
Zhi-Hua Zhou
Zhi-Hua Zhou Nanjing University
Kevin Chen-Chuan Chang
Kevin Chen-Chuan Chang University of Illinois at Urbana-Champaign
Wu He
Wu He Old Dominion University

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