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ICMLA
2007
15 years 6 months ago
Scalable optimal linear representation for face and object recognition
Optimal Component Analysis (OCA) is a linear method for feature extraction and dimension reduction. It has been widely used in many applications such as face and object recognitio...
Yiming Wu, Xiuwen Liu, Washington Mio
LREC
2008
98views Education» more  LREC 2008»
15 years 6 months ago
Producing a Test Collection for Patent Machine Translation in the Seventh NTCIR Workshop
In aiming at research and development on machine translation, we produced a test collection for Japanese-English machine translation in the seventh NTCIR Workshop. This paper desc...
Atsushi Fujii, Masao Utiyama, Mikio Yamamoto, Take...
MVA
2007
207views Computer Vision» more  MVA 2007»
15 years 6 months ago
View-invariant Human Action Recognition Based on Factorization and HMMs
of the fundamental challenges of human action recognition is accounting for the variability that arises during video capturing. For a specific action class, the 2D observations of...
Xi Li, Kazuhiro Fukui
NIPS
2007
15 years 6 months ago
Sparse Feature Learning for Deep Belief Networks
Unsupervised learning algorithms aim to discover the structure hidden in the data, and to learn representations that are more suitable as input to a supervised machine than the ra...
Marc'Aurelio Ranzato, Y-Lan Boureau, Yann LeCun
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NIPS
2004
15 years 6 months ago
Efficient Kernel Discriminant Analysis via QR Decomposition
Linear Discriminant Analysis (LDA) is a well-known method for feature extraction and dimension reduction. It has been used widely in many applications such as face recognition. Re...
Tao Xiong, Jieping Ye, Qi Li, Ravi Janardan, Vladi...