An efficient Kernel-based matrixized least squares support vector machine

[1]  Daoqiang Zhang,et al.  Pattern Representation in Feature Extraction and Classifier Design: Matrix Versus Vector , 2008, IEEE Transactions on Neural Networks.

[2]  Songcan Chen,et al.  New Least Squares Support Vector Machines Based on Matrix Patterns , 2007, Neural Processing Letters.

[3]  Lior Wolf,et al.  Modeling Appearances with Low-Rank SVM , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[4]  Yuxiao Hu,et al.  Learning a Spatially Smooth Subspace for Face Recognition , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[5]  Songcan Chen,et al.  Matrix-pattern-oriented Ho-Kashyap classifier with regularization learning , 2007, Pattern Recognit..

[6]  Xuelong Li,et al.  Supervised tensor learning , 2005, Fifth IEEE International Conference on Data Mining (ICDM'05).

[7]  Tian Yongjun and Chen Songcan,et al.  Matrix-Pattern-Oriented Ho-Kashyap Classifier with Regularization Learning , 2005 .

[8]  Daoqiang Zhang,et al.  Feature extraction approaches based on matrix pattern: MatPCA and MatFLDA , 2005, Pattern Recognit. Lett..

[9]  Samy Bengio,et al.  Links between perceptrons, MLPs and SVMs , 2004, ICML.

[10]  Katsuyuki Hagiwara,et al.  Regularization learning, early stopping and biased estimator , 2002, Neurocomputing.

[11]  Gunnar Rätsch,et al.  An introduction to kernel-based learning algorithms , 2001, IEEE Trans. Neural Networks.

[12]  Johan A. K. Suykens,et al.  Least Squares Support Vector Machine Classifiers , 1999, Neural Processing Letters.

[13]  Ulrich H.-G. Kreßel,et al.  Pairwise classification and support vector machines , 1999 .

[14]  David J. Kriegman,et al.  Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection , 1996, ECCV.

[15]  Jian Yang,et al.  Two-dimensional PCA: a new approach to appearance-based face representation and recognition , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[16]  Rich Caruana,et al.  Overfitting in Neural Nets: Backpropagation, Conjugate Gradient, and Early Stopping , 2000, NIPS.

[17]  Nello Cristianini,et al.  Advances in Kernel Methods - Support Vector Learning , 1999 .

[18]  Vladimir Vapnik,et al.  Statistical learning theory , 1998 .

[19]  Lutz Prechelt,et al.  Early Stopping-But When? , 1996, Neural Networks: Tricks of the Trade.

[20]  Lawrence Sirovich,et al.  Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[21]  Alexander Graham,et al.  Kronecker Products and Matrix Calculus: With Applications , 1981 .

[22]  Vladimir Vapnik,et al.  Chervonenkis: On the uniform convergence of relative frequencies of events to their probabilities , 1971 .

[23]  R. Shah,et al.  Least Squares Support Vector Machines , 2022 .