Jun Wang

According to our database, Jun Wang authored at least 28 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Voltran: Unlocking Trust and Confidentiality in Decentralized Federated Learning Aggregation.

Hao Wang, Yichen Cai, Jun Wang, Chuan Ma, Chunpeng Ge, Xiangmou Qu, Lu Zhou

IEEE Trans. Inf. Forensics Secur., 2024

LLM4DSR: Leveraing Large Language Model for Denoising Sequential Recommendation.

Bohao Wang, Feng Liu, Jiawei Chen, Yudi Wu, Xingyu Lou, Jun Wang, Yan Feng, Chun Chen, Can Wang

CoRR, 2024

Distillation Matters: Empowering Sequential Recommenders to Match the Performance of Large Language Models.

Yu Cui, Feng Liu, Pengbo Wang, Bohao Wang, Heng Tang, Yi Wan, Jun Wang, Jiawei Chen

Proceedings of the 18th ACM Conference on Recommender Systems, 2024

DIIT: A Domain-Invariant Information Transfer Method for Industrial Cross-Domain Recommendation.

Heyuan Huang, Xingyu Lou, Chaochao Chen, Pengxiang Cheng, Yue Xin, Chengwei He, Xiang Liu, Jun Wang

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

Selective and collaborative influence function for efficient recommendation unlearning.

Yuyuan Li, Chaochao Chen, Xiaolin Zheng, Yizhao Zhang, Biao Gong, Jun Wang, Linxun Chen

Expert Syst. Appl., December, 2023

VPiP: Values Packing in Paillier for Communication Efficient Oblivious Linear Computations.

Weibin Wu, Jun Wang, Yangpan Zhang, Zhe Liu, Lu Zhou, Xiaodong Lin

IEEE Trans. Inf. Forensics Secur., 2023

Selective and Collaborative Influence Function for Efficient Recommendation Unlearning.

Yuyuan Li, Chaochao Chen, Xiaolin Zheng, Yizhao Zhang, Biao Gong, Jun Wang

CoRR, 2023

UltraRE: Enhancing RecEraser for Recommendation Unlearning via Error Decomposition.

Yuyuan Li, Chaochao Chen, Yizhao Zhang, Weiming Liu, Lingjuan Lyu, Xiaolin Zheng, Dan Meng, Jun Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Differentially Private Sparse Mapping for Privacy-Preserving Cross Domain Recommendation.

Weiming Liu, Xiaolin Zheng, Chaochao Chen, Mengling Hu, Xinting Liao, Fan Wang, Yanchao Tan, Dan Meng, Jun Wang

Proceedings of the 31st ACM International Conference on Multimedia, 2023

Making Users Indistinguishable: Attribute-wise Unlearning in Recommender Systems.

Yuyuan Li, Chaochao Chen, Xiaolin Zheng, Yizhao Zhang, Zhongxuan Han, Dan Meng, Jun Wang

Proceedings of the 31st ACM International Conference on Multimedia, 2023

In-processing User Constrained Dominant Sets for User-Oriented Fairness in Recommender Systems.

Zhongxuan Han, Chaochao Chen, Xiaolin Zheng, Weiming Liu, Jun Wang, Wenjie Cheng, Yuyuan Li

Proceedings of the 31st ACM International Conference on Multimedia, 2023

HyperFed: Hyperbolic Prototypes Exploration with Consistent Aggregation for Non-IID Data in Federated Learning.

Xinting Liao, Weiming Liu, Chaochao Chen, Pengyang Zhou, Huabin Zhu, Yanchao Tan, Jun Wang, Yue Qi

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

FedLRS: A Communication-Efficient Federated Learning Framework With Low-Rank and Sparse Decomposition.

Mingkai Luo, Dan Meng, Jun Wang, Yu Fang, Jiangyong Ying

Proceedings of the 29th IEEE International Conference on Parallel and Distributed Systems, 2023

Backdoor Attack Against Automatic Speaker Verification Models in Federated Learning.

Dan Meng, Xue Wang, Jun Wang

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

CryptoRec: Novel Collaborative Filtering Recommender Made Privacy-Preserving Easy.

Jun Wang, Chao Jin, Qiang Tang, Zhe Liu, Khin Mi Mi Aung

IEEE Trans. Dependable Secur. Comput., 2022

2021

Recommendation Fairness: From Static to Dynamic.

Dell Zhang, Jun Wang

CoRR, 2021

Popcorn: Paillier Meets Compression For Efficient Oblivious Neural Network Inference.

Jun Wang, Chao Jin, Souhail Meftah, Khin Mi Mi Aung

CoRR, 2021

Automatic test suite generation for key-points detection DNNs using many-objective search (experience paper).

Fitash Ul Haq, Donghwan Shin, Lionel C. Briand, Thomas Stifter, Jun Wang

Proceedings of the ISSTA '21: 30th ACM SIGSOFT International Symposium on Software Testing and Analysis, 2021

2020

Automatic Test Suite Generation for Key-points Detection DNNs Using Many-Objective Search.

Fitash Ul Haq, Donghwan Shin, Lionel C. Briand, Thomas Stifter, Jun Wang

CoRR, 2020

2019

Novel Collaborative Filtering Recommender Friendly to Privacy Protection.

Jun Wang, Qiang Tang, Afonso Arriaga, Peter Y. A. Ryan

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018

Privacy-preserving Recommender Systems Facilitated By The Machine Learning Approach.

Jun Wang

PhD thesis, 2018

Privacy-Preserving Friendship-Based Recommender Systems.

Qiang Tang, Jun Wang

IEEE Trans. Dependable Secur. Comput., 2018

CryptoRec: Secure Recommendations as a Service.

Jun Wang, Afonso Arriaga, Qiang Tang, Peter Y. A. Ryan

CoRR, 2018

Facilitating Privacy-preserving Recommendation-as-a-Service with Machine Learning.

Jun Wang, Afonso Arriaga, Qiang Tang, Peter Y. A. Ryan

Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security, 2018

2017

Differentially Private Neighborhood-Based Recommender Systems.

Jun Wang, Qiang Tang

Proceedings of the ICT Systems Security and Privacy Protection, 2017

2016

A Probabilistic View of Neighborhood-Based Recommendation Methods.

Jun Wang, Qiang Tang

Proceedings of the IEEE International Conference on Data Mining Workshops, 2016

2015

Recommender Systems and their Security Concerns.

Jun Wang, Qiang Tang

IACR Cryptol. ePrint Arch., 2015

Privacy-preserving Context-aware Recommender Systems: Analysis and New Solutions.

Qiang Tang, Jun Wang

IACR Cryptol. ePrint Arch., 2015