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20172023
most citedDifferential Private Knowledge Transfer for Privacy-Preserving Cross-Domain Recommendation

91 citations · 183 across the 22 of their papers we have counts for

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8 papers · 1 filter

cs.LG2022★ 9 cited

A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection

Bingzhe Wu, Jintang Li, Junchi Yu +17

Deep graph learning has achieved remarkable progresses in both business and scientific areas ranging from finance and e-commerce, to drug and advanced material discovery. Despite t…

cs.LG2022★ 91 cited

Differential Private Knowledge Transfer for Privacy-Preserving Cross-Domain Recommendation

Chaochao Chen, Huiwen Wu, Jiajie Su +3

Cross Domain Recommendation (CDR) has been popularly studied to alleviate the cold-start and data sparsity problem commonly existed in recommender systems. CDR models can improve t…

cs.LG2021

Towards Secure and Practical Machine Learning via Secret Sharing and Random Permutation

Fei Zheng, Chaochao Chen, Xiaolin Zheng +1

With the increasing demands for privacy protection, privacy-preserving machine learning has been drawing much attention in both academia and industry. However, most existing method…

cs.LG2020★ 1 cited

Towards Scalable and Privacy-Preserving Deep Neural Network via Algorithmic-Cryptographic Co-design

Jun Zhou, Longfei Zheng, Chaochao Chen +6

Deep Neural Networks (DNNs) have achieved remarkable progress in various real-world applications, especially when abundant training data are provided. However, data isolation has b…

cs.LG2020★ 21 cited

Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification

Chaochao Chen, Jun Zhou, Longfei Zheng +7

Recently, Graph Neural Network (GNN) has achieved remarkable progresses in various real-world tasks on graph data, consisting of node features and the adjacent information between…

cs.LG2020★ 1 cited

Semi-supervised Learning Meets Factorization: Learning to Recommend with Chain Graph Model

Chaochao Chen, Kevin C. Chang, Qibing Li +1

Recently latent factor model (LFM) has been drawing much attention in recommender systems due to its good performance and scalability. However, existing LFMs predict missing values…

cs.LG2019★ 3 cited

Adaptive Portfolio by Solving Multi-armed Bandit via Thompson Sampling

Mengying Zhu, Xiaolin Zheng, Yan Wang +2

As the cornerstone of modern portfolio theory, Markowitz's mean-variance optimization is considered a major model adopted in portfolio management. However, due to the difficulty of…

cs.LG2017★ 6 cited

Neural Collaborative Autoencoder

Qibing Li, Xiaolin Zheng, Xinyue Wu

In recent years, deep neural networks have yielded state-of-the-art performance on several tasks. Although some recent works have focused on combining deep learning with recommenda…