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AAAI
2010
14 years 10 months ago
Multi-Task Sparse Discriminant Analysis (MtSDA) with Overlapping Categories
Multi-task learning aims at combining information across tasks to boost prediction performance, especially when the number of training samples is small and the number of predictor...
Yahong Han, Fei Wu, Jinzhu Jia, Yueting Zhuang, Bi...
PAA
2008
14 years 9 months ago
Online nonparametric discriminant analysis for incremental subspace learning and recognition
This paper presents a novel approach for online subspace learning based on an incremental version of the nonparametric discriminant analysis (NDA). For many real-world applications...
Bogdan Raducanu, Jordi Vitrià
PR
2008
144views more  PR 2008»
14 years 9 months ago
Kernel quadratic discriminant analysis for small sample size problem
It is generally believed that quadratic discriminant analysis (QDA) can better fit the data in practical pattern recognition applications compared to linear discriminant analysis ...
Jie Wang, Konstantinos N. Plataniotis, Juwei Lu, A...
IJON
2010
150views more  IJON 2010»
14 years 8 months ago
Linear discriminant analysis using rotational invariant L1 norm
Linear Discriminant Analysis (LDA) is a well-known scheme for supervised subspace learning. It has been widely used in the applications of computer vision and pattern recognition....
Xi Li, Weiming Hu, Hanzi Wang, Zhongfei Zhang
PAMI
2011
14 years 4 months ago
Kernel Optimization in Discriminant Analysis
— Kernel mapping is one of the most used approaches to intrinsically derive nonlinear classifiers. The idea is to use a kernel function which maps the original nonlinearly separ...
Di You, Onur C. Hamsici, Aleix M. Martínez