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» Metric and Kernel Learning Using a Linear Transformation
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ICIP
2005
IEEE
16 years 3 months ago
Visual tracking via efficient kernel discriminant subspace learning
Robustly tracking moving objects in video sequences is one of the key problems in computer vision. In this paper we introduce a computationally efficient nonlinear kernel learning...
Chunhua Shen, Anton van den Hengel, Michael J. Bro...
ICML
2007
IEEE
16 years 2 months ago
Regression on manifolds using kernel dimension reduction
We study the problem of discovering a manifold that best preserves information relevant to a nonlinear regression. Solving this problem involves extending and uniting two threads ...
Jens Nilsson, Fei Sha, Michael I. Jordan
CVPR
2010
IEEE
15 years 5 months ago
Large-Scale Image Categorization with Explicit Data Embedding
Kernel machines rely on an implicit mapping of the data such that non-linear classification in the original space corresponds to linear classification in the new space. As kernel ...
Florent Perronnin, Jorge Sanchez, Yan Liu
91
Voted
ICDM
2003
IEEE
105views Data Mining» more  ICDM 2003»
15 years 7 months ago
SVM Based Models for Predicting Foreign Currency Exchange Rates
Support vector machine (SVM) has appeared as a powerful tool for forecasting forex market and demonstrated better performance over other methods, e.g., neural network or ARIMA bas...
Joarder Kamruzzaman, Ruhul A. Sarker, Iftekhar Ahm...
116
Voted
JIIS
2006
73views more  JIIS 2006»
15 years 1 months ago
Using KCCA for Japanese-English cross-language information retrieval and document classification
Kernel Canonical Correlation Analysis (KCCA) is a method of correlating linear relationship between two variables in a kernel defined feature space. A machine learning algorithm b...
Yaoyong Li, John Shawe-Taylor