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ICML
2009
IEEE
15 years 10 months ago
Geometry-aware metric learning
In this paper, we introduce a generic framework for semi-supervised kernel learning. Given pairwise (dis-)similarity constraints, we learn a kernel matrix over the data that respe...
Zhengdong Lu, Prateek Jain, Inderjit S. Dhillon
JMIV
2010
115views more  JMIV 2010»
14 years 8 months ago
Image and Video Colorization Using Vector-Valued Reproducing Kernel Hilbert Spaces
Motivated by the setting of reproducing kernel Hilbert space (RKHS) and its extensions considered in machine learning, we propose an RKHS framework for image and video colorizatio...
Minh Ha Quang, Sung Ha Kang, Triet M. Le
CVPR
2008
IEEE
15 years 12 months ago
Parameterized Kernel Principal Component Analysis: Theory and applications to supervised and unsupervised image alignment
Parameterized Appearance Models (PAMs) (e.g. eigentracking, active appearance models, morphable models) use Principal Component Analysis (PCA) to model the shape and appearance of...
Fernando De la Torre, Minh Hoai Nguyen
ICML
2007
IEEE
15 years 10 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
ICML
2008
IEEE
15 years 10 months ago
A reproducing kernel Hilbert space framework for pairwise time series distances
A good distance measure for time series needs to properly incorporate the temporal structure, and should be applicable to sequences with unequal lengths. In this paper, we propose...
Zhengdong Lu, Todd K. Leen, Yonghong Huang, Deniz ...