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» A Kernel Approach to Comparing Distributions
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AAAI
2007
13 years 6 months ago
A Kernel Approach to Comparing 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 Reprod...
Arthur Gretton, Karsten M. Borgwardt, Malte J. Ras...
IROS
2009
IEEE
186views Robotics» more  IROS 2009»
13 years 11 months ago
A statistical approach to gas distribution modelling with mobile robots - The Kernel DM+V algorithm
— Gas distribution modelling constitutes an ideal application area for mobile robots, which – as intelligent mobile gas sensors – offer several advantages compared to station...
Achim J. Lilienthal, Matteo Reggente, Marco Trinca...
CVPR
2011
IEEE
12 years 8 months ago
Kernelized Structural SVM Learning for Supervised Object Segmentation
Object segmentation needs to be driven by top-down knowledge to produce semantically meaningful results. In this paper, we propose a supervised segmentation approach that tightly ...
Luca Bertelli, Tianli Yu, Diem Vu, Salih Gokturk
IJCNN
2006
IEEE
13 years 10 months ago
Comparing Kernels for Predicting Protein Binding Sites from Amino Acid Sequence
— The ability to identify protein binding sites and to detect specific amino acid residues that contribute to the specificity and affinity of protein interactions has importan...
Feihong Wu
COMPGEOM
2011
ACM
12 years 8 months ago
Comparing distributions and shapes using the kernel distance
Starting with a similarity function between objects, it is possible to define a distance metric (the kernel distance) on pairs of objects, and more generally on probability distr...
Sarang C. Joshi, Raj Varma Kommaraju, Jeff M. Phil...