Dispensability of Bias for Three-layer Max-min Fuzzy Neural Networks. - Jie Yang 007; Long Li; Yan Liu 015 (ICNC (1), 2007)

Choice of initial bias in max-min fuzzy neural networks. - Jie Yang 007; Long Li; Yan Liu 015; Jing Wang; Wei Wu 010 (IJCNN, 2010)

A modified gradient-based neuro-fuzzy learning algorithm and its convergence. - Wei Wu 010; Long Li; Jie Yang 007; Yan Liu 015 (Inf. Sci., 2010)

Data-Driven 4D Visualization for Simulating Highway Construction Processes. - Guojun Chen; Yan Liu 015; Jingxiang Chen; Wei Wu 008 (PADS, 2012)

Negative effects of sufficiently small initialweights on back-propagation neural networks. - Yan Liu 015; Jie Yang 007; Long Li; Wei Wu 010 (J. Zhejiang Univ. Sci. C, 2012)

The Binary Output Units of Neural Network. - Qilin Sun 004; Yan Liu 015; Zhengxue Li; Sibo Yang; Wei Wu 010; Jiuwu Jin (ISNN (1), 2013)

A modified gradient learning algorithm with smoothing L1/2 regularization for Takagi-Sugeno fuzzy models. - Yan Liu 015; Wei Wu 010; Qin-wei Fan; Dakun Yang; Jian Wang 010 (Neurocomputing, 2014)

Batch gradient method with smoothing L1/2 regularization for training of feedforward neural networks. - Wei Wu 010; Qin-wei Fan; Jacek M. Zurada; Jian Wang 010; Dakun Yang; Yan Liu 015 (Neural Networks, 2014)

Convergence of batch gradient learning algorithm with smoothing L1/2 regularization for Sigma-Pi-Sigma neural networks. - Yan Liu 015; Zhengxue Li; Dakun Yang; Kh. Sh. Mohamed; Jing Wang; Wei Wu 010 (Neurocomputing, 2015)

A Modified Learning Algorithm for Interval Perceptrons with Interval Weights. - Dakun Yang; Zhengxue Li; Yan Liu 015; Huisheng Zhang; Wei Wu 010 (Neural Process. Lett., 2015)

A Dynamic Energy Balance Method for Wireless Sensor Networks with Small World Characteristics. - Peng Geng; Yan Liu 015; Jie Yang 002 (ICNCC, 2016)

Strong Convergence Analysis of Batch Gradient-Based Learning Algorithm for Training Pi-Sigma Network Based on TSK Fuzzy Models. - Yan Liu 015; Dakun Yang; Nan Nan; Li Guo 008; Jianjun Zhang (Neural Process. Lett., 2016)

Input Layer Regularization of Multilayer Feedforward Neural Networks. - Feng Li 006; Jacek M. Zurada; Yan Liu 015; Wei Wu 010 (IEEE Access, 2017)

Convergence analysis of the batch gradient-based neuro-fuzzy learning algorithm with smoothing L1/2 regularization for the first-order Takagi-Sugeno system. - Yan Liu 015; Dakun Yang (Fuzzy Sets Syst., 2017)

A convergent smoothing algorithm for training max -min fuzzy neural networks. - Long Li; Zhijun Qiao; Yan Liu 015; Yuan Chen (Neurocomputing, 2017)

Robustness of classification ability of spiking neural networks. - Jie Yang 007; Pingping Zhang; Yan Liu 015 (CoRR, 2018)

A Modified Sigma-Pi-Sigma Neural Network with Adaptive Choice of Multinomials. - Feng Li 006; Yan Liu 015; Khidir Shaib Mohamed; Wei Wu 010 (CoRR, 2018)

Boundedness and convergence of split complex gradient descent algorithm with momentum and regularizer for TSK fuzzy models. - Yan Liu 015; Long Li; Dakun Yang (Neurocomputing, 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)

L1/2 regularization learning for smoothing interval neural networks: Algorithms and convergence analysis. - Dakun Yang; Yan Liu 015 (Neurocomputing, 2018)

Smoothed L1/2 regularizer learning for split-complex valued neuro-fuzzy algorithm for TSK system and its convergence results. - Yan Liu 015; Dakun Yang; Feng Li 006 (J. Frankl. Inst., 2018)

A New Conjugate Gradient Method with Smoothing L1/2 Regularization Based on a Modified Secant Equation for Training Neural Networks. - Wenyu Li; Yan Liu 015; Jie Yang 007; Wei Wu 010 (Neural Process. Lett., 2018)

Deep mutual learning for visual tracking. - Kai Gao; Pingping Zhang; Yan Liu 015; Ziqin Zhou; Gang Yang 002; Huchuan Lu (ACM TUR-C, 2019)

Strong Convergence of Neuro-Fuzzy Learning With Adaptive Momentum for Complex System. - Yan Liu 015; Fang Liu; Long Li (IEEE Access, 2019)

An adaptive neuro-complex-fuzzy-inferential modeling mechanism for generating higher-order TSK models. - Yan Liu 015; Fang Liu (Neurocomputing, 2019)

A Split-Complex Valued Gradient-Based Descent Neuro-Fuzzy Algorithm for TS System and Its Convergence. - Yan Liu 015; Dakun Yang; Long Li; Jie Yang 002 (Neural Process. Lett., 2019)

Semi-supervised Crowd Counting via Self-training on Surrogate Tasks. - Yan Liu 015; Lingqiao Liu; Peng Wang 023; Pingping Zhang; Yinjie Lei (ECCV (15), 2020)

Towards using count-level weak supervision for crowd counting. - Yinjie Lei; Yan Liu 015; Pingping Zhang; Lingqiao Liu (Pattern Recognit., 2021)