Convergence of Online Gradient Algorithm with Stochastic Inputs for Pi-Sigma Neural Networks. - Xidai Kang; Yan Xiong; Chao Zhang 017; Wei Wu 010 (FOCI, 2007)

Training Pi-Sigma Network by Online Gradient Algorithm with Penalty for Small Weight Update. - Yan Xiong; Wei Wu 010; Xidai Kang; Chao Zhang 017 (Neural Comput., 2007)

Convergence Analysis of Batch Gradient Algorithm for Three Classes of Sigma-Pi Neural Networks. - Chao Zhang 017; Wei Wu 010; Yan Xiong (Neural Process. Lett., 2007)

Error Bounds for Real Function Classes Based on Discretized Vapnik-Chervonenkis Dimensions. - Chao Zhang 017; Dacheng Tao (Aust. J. Intell. Inf. Process. Syst., 2010)

Risk Bounds for Levy Processes in the PAC-Learning Framework. - Chao Zhang 017; Dacheng Tao (AISTATS, 2010)

Risk Bounds for Infinitely Divisible Distribution. - Chao Zhang 017; Dacheng Tao (UAI, 2011)

Generalization Bound for Infinitely Divisible Empirical Process. - Chao Zhang 017; Dacheng Tao (AISTATS, 2011)

Binary Higher Order Neural Networks for Realizing Boolean Functions. - Chao Zhang 017; Jie Yang 007; Wei Wu 010 (IEEE Trans. Neural Networks, 2011)

Discretized-Vapnik-Chervonenkis Dimension for Analyzing Complexity of Real Function Classes. - Chao Zhang 017; Wei Bian; Dacheng Tao; Weisi Lin (IEEE Trans. Neural Networks Learn. Syst., 2012)

Generalization Bounds of ERM-Based Learning Processes for Continuous-Time Markov Chains. - Chao Zhang 017; Dacheng Tao (IEEE Trans. Neural Networks Learn. Syst., 2012)

Risk bounds of learning processes for Lévy processes. - Chao Zhang 017; Dacheng Tao (J. Mach. Learn. Res., 2013)

Structure of Indicator Function Classes With Finite Vapnik-Chervonenkis Dimensions. - Chao Zhang 017; Dacheng Tao (IEEE Trans. Neural Networks Learn. Syst., 2013)

Task-group Relatedness and Generalization Bounds for Regularized Multi-task Learning. - Chao Zhang 017; Dacheng Tao; Tao Hu 001; Xiang Li (CoRR, 2014)

LSV-Based Tail Inequalities for Sums of Random Matrices. - Chao Zhang 017; Lei Du; Dacheng Tao (Neural Comput., 2017)

Matrix Infinitely Divisible Series: Tail Inequalities and Applications in Optimization. - Chao Zhang 017; Xianjie Gao; Min-Hsiu Hsieh; Hanyuan Hang; Dacheng Tao (CoRR, 2018)

Generalization Bounds for Vicinal Risk Minimization Principle. - Chao Zhang 017; Min-Hsiu Hsieh; Dacheng Tao (CoRR, 2018)

Relaxed conditions for convergence analysis of online back-propagation algorithm with L2 regularizer for Sigma-Pi-Sigma neural network. - Yan Liu 015; Dakun Yang; Chao Zhang 017 (Neurocomputing, 2018)

Binary Output Layer of Feedforward Neural Networks for Solving Multi-Class Classification Problems. - Sibo Yang; Chao Zhang 017; Wei Wu 010 (IEEE Access, 2019)

A Data-Driven Framework for Tunnel Geological-Type Prediction Based on TBM Operating Data. - Junhong Zhao; Maolin Shi; Gang Hu; Xueguan Song; Chao Zhang 017; Dacheng Tao; Wei Wu 010 (IEEE Access, 2019)

On Dimension-free Tail Inequalities for Sums of Random Matrices and Applications. - Chao Zhang 017; Min-Hsiu Hsieh; Dacheng Tao (CoRR, 2019)

Small-Deviation Inequalities for Sums of Random Matrices. - Xianjie Gao; Chao Zhang 017; Hongwei Zhang (Symmetry, 2019)

A Genetic XK-Means Algorithm with Empty Cluster Reassignment. - Chun Hua; Feng Li 006; Chao Zhang 017; Jie Yang 007; Wei Wu 010 (Symmetry, 2019)

Binary Output Layer of Extreme Learning Machine for Solving Multi-class Classification Problems. - Sibo Yang; Chao Zhang 017; Yuan Bao; Jie Yang 007; Wei Wu 010 (Neural Process. Lett., 2020)

Matrix Infinitely Divisible Series: Tail Inequalities and Their Applications. - Chao Zhang 017; Xianjie Gao; Min-Hsiu Hsieh; Hanyuan Hang; Dacheng Tao (IEEE Trans. Inf. Theory, 2020)

Real-time Forecast Models for TBM Load Parameters Based on Machine Learning Methods. - Xianjie Gao; Xueguan Song; Maolin Shi; Chao Zhang 017; Hongwei Zhang (CoRR, 2021)

GAN-MDF: A Method for Multi-fidelity Data Fusion in Digital Twins. - Lixue Liu; Chao Zhang 017; Dacheng Tao (CoRR, 2021)

Hierarchical regression framework for multi-fidelity modeling. - Yueqi Xu; Xueguan Song; Chao Zhang 017 (Knowl. Based Syst., 2021)

A New Oversampling Method Based on the Classification Contribution Degree. - Zhenhao Jiang; Tingting Pan; Chao Zhang 017; Jie Yang 007 (Symmetry, 2021)

Generalization Bounds of Multitask Learning From Perspective of Vector-Valued Function Learning. - Chao Zhang 017; Dacheng Tao; Tao Hu 001; Bingchen Liu (IEEE Trans. Neural Networks Learn. Syst., 2021)

Revisiting PINNs: Generative Adversarial Physics-informed Neural Networks and Point-weighting Method. - Wensheng Li; Chao Zhang 017; Chuncheng Wang; Hanting Guan; Dacheng Tao (CoRR, 2022)

GAN-MDF: An Enabling Method for Multifidelity Data Fusion. - Lixue Liu; Xueguan Song; Chao Zhang 017; Dacheng Tao (IEEE Internet Things J., 2022)

RSAL-iMFS: A framework of randomized stacking with active learning for incremental multi-fidelity surrogate modeling. - Zongqi Liu; Xueguan Song; Chao Zhang 017; Yunsheng Ma; Dacheng Tao (Eng. Appl. Artif. Intell., 2023)

Coding Method Based on Fuzzy C-Means Clustering for Spiking Neural Network With Triangular Spike Response Function. - Fang Liu 017; Witold Pedrycz; Chao Zhang 017; Jie Yang 007; Wei Wu 010 (IEEE Trans. Fuzzy Syst., 2023)

Generative adversarial networks for multi-fidelity matrix completion with massive missing entries. - Zongqi Liu; Xueguan Song; Jie Yang 007; Chao Zhang 017; Dacheng Tao (Inf. Fusion, 2024)

Zero-order fuzzy neural network with adaptive fuzzy partition and its applications on high-dimensional problems. - Bingjie Zhang 001; Jian Wang 010; Chao Zhang 017; Jie Yang 007; Tufan Kumbasar; Wei Wu 010 (Neurocomputing, 2024)

A New Oversampling Method Based on Triangulation of Sample Space. - Yueqi Chen; Witold Pedrycz; Jian Wang 010; Chao Zhang 017; Jie Yang 007 (IEEE Trans. Syst. Man Cybern. Syst., 2024)

Generative adversarial physics-informed neural networks for solving forward and inverse problem with small labeled samples. - Wensheng Li; Chuncheng Wang; Hanting Guan; Jian Wang 010; Jie Yang 007; Chao Zhang 017; Dacheng Tao (Comput. Math. Appl., 2025)

Multifidelity Data Fusion Mechanism for Digital Twins via the Internet of Things. - Hao Wang 003; Xueguan Song; Chao Zhang 017 (IEEE Internet Comput., 2025)

Interpretable inverse iteration mean shift networks for clustering tasks. - Bingjie Zhang 001; Zihan Yu; Jian Wang 010; Maciej Zelaszczyk; Yaqian Zhang; Jacek Mandziuk; Chao Zhang 017; Witold Pedrycz (Neural Networks, 2025)