Estimation of Distribution with Restricted Boltzmann Machine for Adaptive Service Composition. - Shunshun Peng; Hongbing Wang; Qi Yu 001 (ICWS, 2017)

A parallel refined probabilistic approach for QoS-aware service composition. - Hongbing Wang; Shunshun Peng; Qi Yu 001 (Future Gener. Comput. Syst., 2019)

Multi-Clusters Adaptive Brain Storm Optimization Algorithm for QoS-Aware Service Composition. - Shunshun Peng; Hongbing Wang; Qi Yu 001 (IEEE Access, 2020)

Locally Differentially Private Frequent Pattern Mining for High-Dimensional Data in Mobile Smart Services. - Qi Li; Shunshun Peng; Haonan Wu; Ruisheng Ran; Yong Li 023; Mingliang Zhou 001; Taolin Guo; Qin Mao (Int. J. Pattern Recognit. Artif. Intell., 2022)

Community-based social recommendation under local differential privacy protection. - Taolin Guo; Shunshun Peng; Yong Li 023; Mingliang Zhou 001; Trieu-Kien Truong (Inf. Sci., 2023)

RDPCF: Range-based differentially private user data perturbation for collaborative filtering. - Taolin Guo; Shunshun Peng; Kai Dong 001; You Zhao; Mingliang Zhou 001 (Comput. Secur., 2023)

Mining frequent items from high-dimensional set-valued data under local differential privacy protection. - Haonan Wu; Ruisheng Ran; Shunshun Peng; Mengmeng Yang 002; Taolin Guo (Expert Syst. Appl., 2023)

Improving the Accuracy of Locally Differentially Private Community Detection by Order-consistent Data Perturbation. - Taolin Guo; Shunshun Peng; Zhejian Zhang; Mengmeng Yang 002; Kwok-Yan Lam (SIGIR, 2024)

Representation Learning Based on Vision Transformer. - Ruisheng Ran; Tianyu Gao; Qianwei Hu; Wenfeng Zhang; Shunshun Peng; Bin Fang 001 (Int. J. Pattern Recognit. Artif. Intell., 2024)

LDP-PPA: Local differential privacy protection for principal component analysis. - Shunshun Peng; Haoqi Li; Wenhao Wang; Kai Dong 001; Mengmeng Yang 002; Taolin Guo (Inf. Sci., 2025)