Liver cancer identification based on PSO-SVM model. - Huiyan Jiang; Fengzhen Tang; Xiyue Zhang (ICARCV, 2010)

Model-based kernel for efficient time series analysis. - Huanhuan Chen; Fengzhen Tang; Peter Tiño; Xin Yao 001 (KDD, 2013)

Support Vector Ordinal Regression using Privileged Information. - Fengzhen Tang; Peter Tiño; Pedro Antonio Gutiérrez; Huanhuan Chen (ESANN, 2014)

Learning the deterministically constructed Echo State Networks. - Fengzhen Tang; Peter Tiño; Huanhuan Chen (IJCNN, 2014)

Model Metric Co-Learning for Time Series Classification. - Huanhuan Chen; Fengzhen Tang; Peter Tiño; Anthony G. Cohn 001; Xin Yao 001 (IJCAI, 2015)

The Benefits of Modeling Slack Variables in SVMs. - Fengzhen Tang; Peter Tiño; Pedro Antonio Gutiérrez; Huanhuan Chen (Neural Comput., 2015)

Kernel methods for time series data. - Fengzhen Tang (2015)

A prey-predator model for efficient robot tracking. - Fengzhen Tang; Bailu Si; Daxiong Ji (ICRA, 2017)

Model learning based on grid cell representations. - Guanwen Huang; Bailu Si; Fengzhen Tang (ROBIO, 2017)

Ordinal regression based on learning vector quantization. - Fengzhen Tang; Peter Tiño (Neural Networks, 2017)

Group feature selection with multiclass support vector machine. - Fengzhen Tang; Lukás Adam; Bailu Si (Neurocomputing, 2018)

Unsupervised Feature Learning for Visual Place Recognition in Changing Environments. - Dongye Zhao; Bailu Si; Fengzhen Tang (IJCNN, 2019)

Scan registration for underwater mechanical scanning imaging sonar using symmetrical Kullback-Leibler divergence. - Min Jiang; Sanming Song; Fengzhen Tang; Yiping Li; Jian Liu; Xisheng Feng (J. Electronic Imaging, 2019)

Learning joint space-time-frequency features for EEG decoding on small labeled data. - Dongye Zhao; Fengzhen Tang; Bailu Si; Xisheng Feng (Neural Networks, 2019)

NeuroBayesSLAM: Neurobiologically inspired Bayesian integration of multisensory information for robot navigation. - Taiping Zeng; Fengzhen Tang; Daxiong Ji; Bailu Si (Neural Networks, 2020)

A novel oversampling technique based on the manifold distance for class imbalance learning. - Yinan Guo 001; Botao Jiao; Lingkai Yang; Jian Cheng 004; Shengxiang Yang; Fengzhen Tang (Int. J. Bio Inspired Comput., 2021)

Probabilistic learning vector quantization on manifold of symmetric positive definite matrices. - Fengzhen Tang; Haifeng Feng; Peter Tino; Bailu Si; Daxiong Ji (Neural Networks, 2021)

Feature selection with kernelized multi-class support vector machine. - Yinan Guo 001; Zirui Zhang; Fengzhen Tang (Pattern Recognit., 2021)

Generalized Learning Riemannian Space Quantization: A Case Study on Riemannian Manifold of SPD Matrices. - Fengzhen Tang; Mengling Fan; Peter Tiño (IEEE Trans. Neural Networks Learn. Syst., 2021)

A transfer weighted extreme learning machine for imbalanced classification. - Yinan Guo 001; Botao Jiao; Ying Tan 002; Pei Zhang 014; Fengzhen Tang (Int. J. Intell. Syst., 2022)

Nonstationary fuzzy neural network based on FCMnet clustering and a modified CG method with Armijo-type rule. - Bingjie Zhang 001; Xiaoling Gong; Jian Wang 010; Fengzhen Tang; Kai Zhang 029; Wei Wu 010 (Inf. Sci., 2022)

Riemannian dynamic generalized space quantization learning. - Mengling Fan; Fengzhen Tang; Yinan Guo 001; Xingang Zhao (Pattern Recognit., 2022)

Prototype based linear sub-manifold learning. - Mengling Fan; Fengzhen Tang; Xingang Zhao (IJCNN, 2023)

Generalized Learning Vector Quantization With Log-Euclidean Metric Learning on Symmetric Positive-Definite Manifold. - Fengzhen Tang; Peter Tino; Haibin Yu (IEEE Trans. Cybern., 2023)

Knowledge-based hybrid connectionist models for morphologic reasoning. - Kai He; Wenxue Wang; Gang Li; Peng Yu; Fengzhen Tang; Ning Xi 001; Lianqing Liu (Mach. Vis. Appl., 2023)

Vibration optimization of cantilevered bistable composite shells based on machine learning. - Chenchen Wu; Ruming Zhang; Fengzhen Tang; Mengling Fan (Eng. Appl. Artif. Intell., 2023)

Dimension selection for EEG classification in the SPD Riemannian space based on PSO. - Zirui Zhang; Yinan Guo; Fengzhen Tang (Knowl. Based Syst., 2023)

Time Window Optimization for Riemannian Geometry-based Motor Imagery EEG Classification. - Fanbo Zhuo; Bo Lv; Fengzhen Tang (EMBC, 2024)

Addressing Intermediate Verification Latency in Online Learning Through Immediate Pseudo-labeling and Oriented Synthetic Correction. - Zixin Zhong; Liyan Song; Fengzhen Tang; Bo Yuan (IJCNN, 2024)

A Collaborative Mapping System for a Brain-Inspired SLAM. - Hangpiao Zhao; Tao Li; Zhihui Zhang; Fengzhen Tang (IEEE Internet Things J., 2025)

Robust Soft LVQ With LEML for SPD Matrices. - Fengzhen Tang; Xiaocheng Zhang (IEEE Trans. Emerg. Top. Comput. Intell., 2025)