Nonlinear component analysis as a kernel eigenvalue problem
Neural Computation
A Generalized Representer Theorem
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
Principal Manifolds and Nonlinear Dimensionality Reduction via Tangent Space Alignment
SIAM Journal on Scientific Computing
IEEE Transactions on Pattern Analysis and Machine Intelligence
General Tensor Discriminant Analysis and Gabor Features for Gait Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Discriminative Locality Alignment
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Geometric Mean for Subspace Selection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Patch Alignment for Dimensionality Reduction
IEEE Transactions on Knowledge and Data Engineering
Recognition of handwritten Chinese characters by critical region analysis
Pattern Recognition
Bregman Divergence-Based Regularization for Transfer Subspace Learning
IEEE Transactions on Knowledge and Data Engineering
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
Max-Min Distance Analysis by Using Sequential SDP Relaxation for Dimension Reduction
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal on Document Analysis and Recognition - Special Issue on Performance Evaluation
Manifold elastic net: a unified framework for sparse dimension reduction
Data Mining and Knowledge Discovery
ICDAR '11 Proceedings of the 2011 International Conference on Document Analysis and Recognition
Ensemble Manifold Regularization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sparse transfer learning for interactive video search reranking
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
IEEE Transactions on Image Processing
An introduction to kernel-based learning algorithms
IEEE Transactions on Neural Networks
Face recognition using LDA-based algorithms
IEEE Transactions on Neural Networks
Non-Negative Patch Alignment Framework
IEEE Transactions on Neural Networks
Subspaces Indexing Model on Grassmann Manifold for Image Search
IEEE Transactions on Image Processing
DAML: Domain Adaptation Metric Learning
IEEE Transactions on Image Processing
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It is essential to extract the discriminative information for similar handwritten Chinese character recognition (SHCCR) that plays a key role to improve the performance of handwritten Chinese character recognition. This paper first introduces a new manifold learning based subspace learning algorithm, discriminative locality alignment (DLA), to SHCCR. Afterward, we propose the kernel version of DLA, kernel discriminative locality alignment (KDLA), and carefully prove that learning KDLA is equal to conducting kernel principal component analysis (KPCA) followed by DLA. This theoretical investigation can be utilized to better understand KDLA, i.e., the subspace spanned by KDLA is essentially the subspace spanned by DLA on the principal components of KPCA. Experimental results demonstrate that DLA and KDLA are more effective than representative discriminative information extraction algorithms in terms of recognition accuracy.