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» Sampling Techniques for Kernel Methods
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ICML
2004
IEEE
15 years 3 months ago
Learning a kernel matrix for nonlinear dimensionality reduction
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul
ICRA
2007
IEEE
147views Robotics» more  ICRA 2007»
15 years 4 months ago
Fixed-lag Sampling Strategies for Particle Filtering SLAM
— We describe two new sampling strategies for Rao-Blackwellized particle filtering SLAM. The strategies, called fixed-lag roughening and the block proposal distribution, both e...
Kristopher R. Beevers, Wesley H. Huang
WSC
1997
14 years 11 months ago
Descriptive Sampling: An Improvement over Latin Hypercube Sampling
Descriptive Sampling (DS), a Monte Carlo sampling technique based on a deterministic selection of the input values and their random permutation, represents a deep conceptual chang...
Eduardo Saliby
SCALESPACE
2001
Springer
15 years 2 months ago
Gaussian Convolutions. Numerical Approximations Based on Interpolation
Abstract. Gaussian convolutions are perhaps the most often used image operators in low-level computer vision tasks. Surprisingly though, there are precious few articles that descri...
Rein van den Boomgaard, Rik van der Weij
CORR
2010
Springer
94views Education» more  CORR 2010»
14 years 7 months ago
Segmented compressed sampling for analog-to-information conversion: Method and performance analysis
A new segmented compressed sampling (CS) method for analog-to-information conversion (AIC) is proposed. An analog signal measured by a number of parallel branches of mixers and int...
Omid Taheri, Sergiy A. Vorobyov