Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Using Discriminant Eigenfeatures for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Matrix computations (3rd ed.)
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Expected classification error of the Fisher linear classifier with pseudo-inverse covariance matrix
Pattern Recognition Letters
Dimensionality reduction for similarity searching in dynamic databases
Computer Vision and Image Understanding - Special issue on content-based access for image and video libraries
Hierarchical Discriminant Regression
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Parameterized Component Analysis
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
SIAM Journal on Matrix Analysis and Applications
Fast and accurate text classification via multiple linear discriminant projections
The VLDB Journal — The International Journal on Very Large Data Bases
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Enhanced Fisher Linear Discriminant Models for Face Recognition
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Discriminative Common Vectors for Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generalized Discriminant Analysis Using a Kernel Approach
Neural Computation
An optimization criterion for generalized discriminant analysis on undersampled problems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition using kernel direct discriminant analysis algorithms
IEEE Transactions on Neural Networks
The theoretical analysis of GLRAM and its applications
Pattern Recognition
Face recognition using a kernel fractional-step discriminant analysis algorithm
Pattern Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Knowledge and Information Systems
Discriminant Subspace Analysis: A Fukunaga-Koontz Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Two-stage optimal component analysis
Computer Vision and Image Understanding
A discriminant analysis for undersampled data
AIDM '07 Proceedings of the 2nd international workshop on Integrating artificial intelligence and data mining - Volume 84
Feature extraction using constrained maximum variance mapping
Pattern Recognition
Locally linear discriminant embedding: An efficient method for face recognition
Pattern Recognition
CAI '07 Proceedings of the 20th conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
A Supervised Subspace Learning Algorithm: Supervised Neighborhood Preserving Embedding
ADMA '07 Proceedings of the 3rd international conference on Advanced Data Mining and Applications
Semi-supervised Discriminant Analysis Via CCCP
ECML PKDD '08 Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II
A note on two-dimensional linear discriminant analysis
Pattern Recognition Letters
Heteroscedastic Probabilistic Linear Discriminant Analysis with Semi-supervised Extension
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
Generalized discriminant analysis: a matrix exponential approach
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A pre-clustering technique for optimizing subclass discriminant analysis
Pattern Recognition Letters
DLDA/QR: a robust direct LDA algorithm for face recognition and its theoretical foundation
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
A scalable two-stage approach for a class of dimensionality reduction techniques
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Robust kernel discriminant analysis using fuzzy memberships
Pattern Recognition
Two-dimensional random projection
Signal Processing
EURASIP Journal on Advances in Signal Processing
A New and Fast Orthogonal Linear Discriminant Analysis on Undersampled Problems
SIAM Journal on Scientific Computing
Fast supervised feature extraction by term discrimination information pooling
Proceedings of the 20th ACM international conference on Information and knowledge management
Pattern classification using composite features
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Gabor feature based classification using LDA/QZ algorithm for face recognition
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
Robust discriminant analysis of latent semantic feature for text categorization
FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
ACII'05 Proceedings of the First international conference on Affective Computing and Intelligent Interaction
A novel fisher criterion based St-subspace linear discriminant method for face recognition
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Image recognition with LPP mixtures
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Resampling LDA/QR and PCA+LDA for face recognition
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Regularized orthogonal linear discriminant analysis
Pattern Recognition
A local tangent space alignment based transductive classification algorithm
ANNPR'06 Proceedings of the Second international conference on Artificial Neural Networks in Pattern Recognition
Feature extraction using fuzzy maximum margin criterion
Neurocomputing
Enhanced fisher discriminant criterion for image recognition
Pattern Recognition
Performance evaluation of subspace methods to tackle small sample size problem in face recognition
Proceedings of the International Conference on Advances in Computing, Communications and Informatics
The Study of Content Security for Mobile Internet
Wireless Personal Communications: An International Journal
Equivalence Between LDA/QR and Direct LDA
International Journal of Cognitive Informatics and Natural Intelligence
Exploiting fisher and fukunaga-koontz transforms in chernoff dimensionality reduction
ACM Transactions on Knowledge Discovery from Data (TKDD)
Dynamic discriminant functions with missing feature values
Pattern Recognition Letters
Global plus local: A complete framework for feature extraction and recognition
Pattern Recognition
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Linear Discriminant Analysis (LDA) is a well-known method for feature extraction and dimension reduction. It has been used widely in many applications involving high-dimensional data, such as image and text classification. An intrinsic limitation of classical LDA is the so-called singularity problems; that is, it fails when all scatter matrices are singular. Many LDA extensions were proposed in the past to overcome the singularity problems. Among these extensions, PCA+LDA, a two-stage method, received relatively more attention. In PCA+LDA, the LDA stage is preceded by an intermediate dimension reduction stage using Principal Component Analysis (PCA). Most previous LDA extensions are computationally expensive, and not scalable, due to the use of Singular Value Decomposition or Generalized Singular Value Decomposition. In this paper, we propose a two-stage LDA method, namely LDA/QR, which aims to overcome the singularity problems of classical LDA, while achieving efficiency and scalability simultaneously. The key difference between LDA/QR and PCA+LDA lies in the first stage, where LDA/QR applies QR decomposition to a small matrix involving the class centroids, while PCA+LDA applies PCA to the total scatter matrix involving all training data points. We further justify the proposed algorithm by showing the relationship among LDA/QR and previous LDA methods. Extensive experiments on face images and text documents are presented to show the effectiveness of the proposed algorithm.