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PAMI
2008
391views more  PAMI 2008»
15 years 6 months ago
Riemannian Manifold Learning
Recently, manifold learning has been widely exploited in pattern recognition, data analysis, and machine learning. This paper presents a novel framework, called Riemannian manifold...
Tong Lin, Hongbin Zha
TNN
2008
105views more  TNN 2008»
15 years 6 months ago
Incremental Learning of Chunk Data for Online Pattern Classification Systems
This paper presents a pattern classification system in which feature extraction and classifier learning are simultaneously carried out not only online but also in one pass where tr...
Seiichi Ozawa, Shaoning Pang, Nikola K. Kasabov
JOCN
2010
109views more  JOCN 2010»
15 years 4 months ago
Learning Shapes the Representation of Visual Categories in the Aging Human Brain
■ The ability to make categorical decisions and interpret sensory experiences is critical for survival and interactions across the lifespan. However, little is known about the h...
Stephen D. Mayhew, Sheng Li, Joshua K. Storrar, Ka...
COLT
2010
Springer
15 years 4 months ago
Learning Rotations with Little Regret
We describe online algorithms for learning a rotation from pairs of unit vectors in Rn . We show that the expected regret of our online algorithm compared to the best fixed rotati...
Elad Hazan, Satyen Kale, Manfred K. Warmuth
PR
2011
14 years 9 months ago
A survey of multilinear subspace learning for tensor data
Increasingly large amount of multidimensional data are being generated on a daily basis in many applications. This leads to a strong demand for learning algorithms to extract usef...
Haiping Lu, Konstantinos N. Plataniotis, Anastasio...