Another neural network based approach for computing eigenvalues and eigenvectors of real skew-symmetric matrices. - Ying Tang 002; Jianping Li (Comput. Math. Appl., 2010)

Notes on "Recurrent neural network model for computing largest and smallest generalized eigenvalue". - Ying Tang 002; Jianping Li (Neurocomputing, 2010)

Normalized natural gradient in independent component analysis. - Ying Tang 002; Jianping Li (Signal Process., 2010)

A Novel Neural Network Approach for Computing Eigen-Pairs of Real Antisymmetric Matrices. - Hang Tan; Xianhe Huang; Huachun Tan; Ying Tang 002 (AICI, 2012)

New ICA Algorithms based on Special linear Group. - Hang Tan; Xianhe Huang; Ying Tang 002; Huachun Tan (Int. J. Model. Simul. Sci. Comput., 2013)

Neural-Network-Based Approach for Extracting Eigenvectors and Eigenvalues of Real Normal Matrices and Some Extension to Real Matrices. - Xiongfei Zou; Ying Tang 002; Shirong Bu; Zhengxiang Luo; Shouming Zhong (J. Appl. Math., 2013)

Pairwise comparisons in spectral ranking. - Ying Tang 002; Yinrun Li (Neurocomputing, 2016)

Independent component analysis employing exponentials of sparse antisymmetric matrices. - Ying Tang 002 (Neurocomputing, 2019)

Iteration on single vector for extracting two extremal eigenpairs of symmetric matrices. - Ying Tang 002; Yuan Tang; Siyu Zhan; Yinrun Li (Neurocomputing, 2019)

Two-hop walks indicate PageRank order. - Ying Tang 002 (Pattern Recognit., 2019)

Fast orthogonal recurrent neural networks employing a novel parametrisation for orthogonal matrices. - Ying Tang 002 (Signal Process., 2019)

Beyond EM: A faster Bayesian linear regression algorithm without matrix inversions. - Ying Tang 002 (Neurocomputing, 2020)