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CIBCB
2005
IEEE
15 years 8 months ago
The Homology Kernel: A Biologically Motivated Sequence Embedding into Euclidean Space
— Part of the challenge of modeling protein sequences is their discrete nature. Many of the most powerful statistical and learning techniques are applicable to points in a Euclid...
Eleazar Eskin, Sagi Snir
IDEAL
2004
Springer
15 years 8 months ago
Kernel Density Construction Using Orthogonal Forward Regression
Abstract— The paper presents an efficient construction algorithm for obtaining sparse kernel density estimates based on a regression approach that directly optimizes model gener...
Sheng Chen, Xia Hong, Chris J. Harris
COLT
2003
Springer
15 years 8 months ago
Maximum Margin Algorithms with Boolean Kernels
Recent work has introduced Boolean kernels with which one can learn linear threshold functions over a feature space containing all conjunctions of length up to k (for any 1 ≤ k ...
Roni Khardon, Rocco A. Servedio
IJON
2007
166views more  IJON 2007»
15 years 2 months ago
Kernel PCA for similarity invariant shape recognition
We present in this paper a novel approach for shape description based on kernel principal component analysis (KPCA). The strength of this method resides in the similarity (rotatio...
Hichem Sahbi
CVPR
2011
IEEE
14 years 10 months ago
What You Saw is Not What You Get: Domain Adaptation Using Asymmetric Kernel Transforms
In real-world applications, “what you saw” during training is often not “what you get” during deployment: the distribution and even the type and dimensionality of features...
Brian Kulis, Kate Saenko, Trevor Darrell