Feature Weighting for RBFNN Based on Genetic Algorithm and Localized Generalization Error Model. - Tianyu Chen; Ting Wang 015; Wing W. Y. Ng; Jianjun Zhang 004 (iThings/GreenCom/CPSCom/SmartData, 2017)

Dual Denoising Autoencoder Features for Imbalance Classification Problems. - Ting Wang 015; Guangjun Zeng; Wing W. Y. Ng; Jinde Li (iThings/GreenCom/CPSCom/SmartData, 2017)

Unsupervised feature selection by regularized matrix factorization. - Miao Qi; Ting Wang 015; Fucong Liu; Baoxue Zhang; Jianzhong Wang; Yugen Yi (Neurocomputing, 2018)

Dual Denoising Autoencoder Feature Learning for Cancer Diagnosis. - Yuqing Gao; Wing W. Y. Ng; Ting Wang 015; Sam Kwong (ICCI*CC, 2019)

Broad Autoencoder Features Learning for Pattern Classification Problems. - Ting Wang 015; Wing W. Y. Ng; Wendi Li; Sam Kwong; Jingde Li (ICCI*CC, 2019)

Multi-Task Learning With Localized Generalization Error Model. - Wendi Li; Yi Zhu; Ting Wang 015; Wing W. Y. Ng (ICMLC, 2019)

Undersampling Near Decision Boundary for Imbalance Problems. - Jianjun Zhang 004; Ting Wang 015; Wing W. Y. Ng; Shuai Zhang 001; Chris D. Nugent (ICMLC, 2019)

Minority Oversampling Using Sensitivity. - Jianjun Zhang 004; Ting Wang 015; Wing W. Y. Ng; Witold Pedrycz; Shuai Zhang 001; Chris D. Nugent (IJCNN, 2020)

Multi-Level Local Feature Coding Fusion for Music Genre Recognition. - Wing W. Y. Ng; Weijie Zeng; Ting Wang 015 (IEEE Access, 2020)

Radial Basis Function Neural Network with Localized Stochastic-Sensitive Autoencoder for Home-Based Activity Recognition. - Wing W. Y. Ng; Shichao Xu; Ting Wang 015; Shuai Zhang 001; Chris D. Nugent (Sensors, 2020)

Broad Autoencoder Features Learning for Classification Problem. - Ting Wang 015; Wing W. Y. Ng; Wendi Li; Sam Kwong (Int. J. Cogn. Informatics Nat. Intell., 2021)

HELP: An LSTM-based approach to hyperparameter exploration in neural network learning. - Wendi Li; Wing W. Y. Ng; Ting Wang 015; Marcello Pelillo; Sam Kwong (Neurocomputing, 2021)

LiSSA: Localized Stochastic Sensitive Autoencoders. - Ting Wang 015; Wing W. Y. Ng; Marcello Pelillo; Sam Kwong (IEEE Trans. Cybern., 2021)

Stochastic Sensitivity Regularized Autoencoder for Robust Feature Learning. - Jianjun Zhang 004; Ting Wang 015; Wing W. Y. Ng; Witold Pedrycz; Sam Kwong (ICCI*CC, 2022)

A Sensitivity-based Pruning Method for Convolutional Neural Networks. - Cankun Zhong; Yang He; Yifei An; Wing W. Y. Ng; Ting Wang 015 (SMC, 2022)

Ensembling perturbation-based oversamplers for imbalanced datasets. - Jianjun Zhang 004; Ting Wang 015; Wing W. Y. Ng; Witold Pedrycz (Neurocomputing, 2022)

A Deep Clustering via Automatic Feature Embedded Learning for Human Activity Recognition. - Ting Wang 015; Wing W. Y. Ng; Jinde Li; Qiuxia Wu; Shuai Zhang 001; Chris D. Nugent; Colin Shewell (IEEE Trans. Circuits Syst. Video Technol., 2022)

Multi-Localized Sensitive Autoencoder-Attention-LSTM For Skeleton-based Action Recognition. - Wing W. Y. Ng; Mingyang Zhang; Ting Wang 015 (IEEE Trans. Multim., 2022)

LSSED: A Robust Segmentation Network for Inflamed Appendix from CT Images. - Wing W. Y. Ng; Peixin Zheng; Ting Wang 015; Jianjun Zhang 004; Yinhao Liang; Hui Zhou; Dan Liang; Guangming Li; Xinhua Wei (ICASSP, 2023)

Moisture Content Prediction of Sugi Wood Drying Using Deep LSTM AE Minimizing Perturbed Error. - Ting Wang 015; Wing W. Y. Ng; Mingyang Zhang; Xueli Zhang; Jianjun Zhang 004; Mingcong Deng (SMC, 2023)

Evaluation of radial basis function neural network minimizing L-GEM for sensor-based activity recognition. - Shuai Zhang 001; Wing W. Y. Ng; Jianjun Zhang 004; Chris D. Nugent; Naomi Irvine; Ting Wang 015 (J. Ambient Intell. Humaniz. Comput., 2023)

Robust recurrent neural networks for time series forecasting. - Xueli Zhang; Cankun Zhong; Jianjun Zhang 004; Ting Wang 015; Wing W. Y. Ng (Neurocomputing, 2023)

Perturbation-based oversampling technique for imbalanced classification problems. - Jianjun Zhang 004; Ting Wang 015; Wing W. Y. Ng; Witold Pedrycz (Int. J. Mach. Learn. Cybern., 2023)

Population-Based Hyperparameter Tuning With Multitask Collaboration. - Wendi Li; Ting Wang 015; Wing W. Y. Ng (IEEE Trans. Neural Networks Learn. Syst., 2023)

KNNENS: A k-Nearest Neighbor Ensemble-Based Method for Incremental Learning Under Data Stream With Emerging New Classes. - Jianjun Zhang 004; Ting Wang 015; Wing W. Y. Ng; Witold Pedrycz (IEEE Trans. Neural Networks Learn. Syst., 2023)

AOCN: Appendix Object Correction Network Utilizing Relationships Across CT Slices. - Wing W. Y. Ng; Jing Xu; Yinhao Liang; Ting Wang 015; Jianjun Zhang 004; Hui Zhou; Dan Liang; Guangming Li; Xinhua Wei (SMC, 2024)

BASS: Broad Network Based on Localized Stochastic Sensitivity. - Ting Wang 015; Mingyang Zhang; Jianjun Zhang 004; Wing W. Y. Ng; C. L. Philip Chen (IEEE Trans. Neural Networks Learn. Syst., 2024)

HRadNet: A Hierarchical Radiomics-Based Network for Multicenter Breast Cancer Molecular Subtypes Prediction. - Yinhao Liang; Wenjie Tang; Ting Wang 015; Wing W. Y. Ng; Siyi Chen; Kuiming Jiang; Xinhua Wei; Xinqing Jiang; Yuan Guo (IEEE Trans. Medical Imaging, 2024)

SBHA: Sensitive Binary Hashing Autoencoder for Image Retrieval. - Ting Wang 015; Su Lu; Jianjun Zhang 004; Xuyu Liu; Xing Tian; Wing W. Y. Ng; Wei-neng Chen (IEEE Trans. Cybern., 2024)

Broad hashing for image retrieval. - Wing W. Y. Ng; Xuyu Liu; Xing Tian; Ting Wang 015; Jianjun Zhang 004; C. L. Philip Chen (Neurocomputing, 2025)

LSSMSD: defending against black-box DNN model stealing based on localized stochastic sensitivity. - Xueli Zhang; Jiale Chen; Qihua Li; Jianjun Zhang 004; Wing W. Y. Ng; Ting Wang 015 (Int. J. Mach. Learn. Cybern., 2025)

XRadNet: A Radiomics-Guided Breast Cancer Molecular Subtype Prediction Network With a Radiomics Explanation. - Yinhao Liang; Wenjie Tang; Jianjun Zhang 004; Ting Wang 015; Wing W. Y. Ng; Siyi Chen; Kuiming Jiang; Xinhua Wei; Xinqing Jiang; Yuan Guo (IEEE J. Biomed. Health Informatics, 2025)