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Yuan Yan Tang
Researcher at University of Macau
Publications - 674
Citations - 15632
Yuan Yan Tang is an academic researcher from University of Macau. The author has contributed to research in topics: Wavelet & Wavelet transform. The author has an hindex of 58, co-authored 647 publications receiving 12835 citations. Previous affiliations of Yuan Yan Tang include Hong Kong Community College & Southwest Baptist University.
Papers
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Hyperspectral Image Classification Based on Regularized Sparse Representation
TL;DR: First, a centralized quadratic constraint as the regularization term is incorporated into the objective function of ℓ1-norm sparse representation model and second, RSR can be effectively solved by the feature-sign search algorithm.
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Combination of activation functions in extreme learning machines for multivariate calibration
TL;DR: A combinational ELM (CELM) method, in which the decision function is represented as a sum of a linear hidden-node output function (activation function) and a nonlinear hidden- node output function, can effectively describe the linear and nonlinear relations existed in spectroscopy regression.
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A collaborative-competitive representation based classifier model
TL;DR: A novel collaborative-competitive representation based classifier model is proposed, which incorporates a regularization constraint term into the objective function of CRC, and it is found that minimizing this constraint term is equivalent to the nearest-subspace classifier (NSC) model.
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The modeling and analysis of the word-of-mouth marketing
TL;DR: In this paper, a dynamic model, known as the SIPNS model, capturing the WOM marketing processes with both positive and negative comments is established, and a measure of the overall profit of a WOM marketing campaign is proposed.
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Minimum Error Entropy Based Sparse Representation for Robust Subspace Clustering
TL;DR: This paper develops a novel subspace clustering method, termed MEESSC, by specifying the minimum error entropy (MEE) as the loss function and the sparsity inducing atomic set and shows that it can well overcome the above limitation.