403 search results - page 19 / 81 » Metric and Kernel Learning Using a Linear Transformation |
103
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NIPS
2003
15 years 3 months ago
2003
We consider the question of predicting nonlinear time series. Kernel Dynamical Modeling (KDM), a new method based on kernels, is proposed as an extension to linear dynamical model...
117
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IJCNN
2000
IEEE
15 years 6 months ago
2000
IEEE
We introduce an algorithm for learning a local metric to a continuous input space that measures distances in terms of relevance to the processing task. The relevance is defined a...
129
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WSCG
2004
15 years 3 months ago
2004
Principal Component Analysis (PCA) is a basis transformation to diagonalize an estimate of the covariance matrix of input data and, the new coordinates in the Eigenvector basis ar...
137
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JMLR
2010
14 years 8 months ago
2010
Kernel techniques have long been used in SVM to handle linearly inseparable problems by transforming data to a high dimensional space, but training and testing large data sets is ...
116
Voted
ICML
2007
IEEE
16 years 2 months ago
2007
IEEE
This paper suggests a method for multiclass learning with many classes by simultaneously learning shared characteristics common to the classes, and predictors for the classes in t...