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» Comparing distributions and shapes using the kernel distance
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PAMI
2011
14 years 8 days ago
Shape Analysis of Elastic Curves in Euclidean Spaces
—This paper introduces a square-root velocity (SRV) representation for analyzing shapes of curves in Euclidean spaces under an elastic metric. Due to this SRV representation the ...
Anuj Srivastava, Eric Klassen, Shantanu H. Joshi, ...
IROS
2007
IEEE
145views Robotics» more  IROS 2007»
15 years 3 months ago
A quantitative method for comparing trajectories of mobile robots using point distribution models
— In the field of mobile robotics, trajectory details are seldom taken into account to qualify robot performance. Most metrics rely mainly on global results such as the total ti...
Pierre Roduit, Alcherio Martinoli, Jacques Jacot
ADMA
2005
Springer
134views Data Mining» more  ADMA 2005»
14 years 11 months ago
An LZ78 Based String Kernel
We develop the notion of normalized information distance (NID) [7] into a kernel distance suitable for use with a Support Vector Machine classifier, and demonstrate its use for an...
Ming Li, Ronan Sleep
DIS
2007
Springer
15 years 3 months ago
A Hilbert Space Embedding for Distributions
We describe a technique for comparing distributions without the need for density estimation as an intermediate step. Our approach relies on mapping the distributions into a reprodu...
Alexander J. Smola, Arthur Gretton, Le Song, Bernh...
SKG
2006
IEEE
15 years 3 months ago
Embedding the Semantic Knowledge in Convolution Kernels
Convolution kernels, such as tree kernel and subsequence kernel are useful for natural language processing tasks. However, most of them ignore the semantic knowledge. In order to ...
Kebin Liu, Fang Li, Ying Han, Lei Liu