Sciweavers

Share
74 search results - page 1 / 15
» Hilbert Space Embeddings and Metrics on Probability Measures
Sort
View
JMLR
2010
118views more  JMLR 2010»
11 years 8 months ago
Hilbert Space Embeddings and Metrics on Probability Measures
A Hilbert space embedding for probability measures has recently been proposed, with applications including dimensionality reduction, homogeneity testing, and independence testing....
Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fu...
COLT
2008
Springer
12 years 3 months ago
Injective Hilbert Space Embeddings of Probability Measures
A Hilbert space embedding for probability measures has recently been proposed, with applications including dimensionality reduction, homogeneity testing and independence testing. ...
Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fu...
DIS
2007
Springer
12 years 8 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...
JMLR
2010
114views more  JMLR 2010»
11 years 8 months ago
On the relation between universality, characteristic kernels and RKHS embedding of measures
Universal kernels have been shown to play an important role in the achievability of the Bayes risk by many kernel-based algorithms that include binary classification, regression, ...
Bharath K. Sriperumbudur, Kenji Fukumizu, Gert R. ...
FOCS
2004
IEEE
12 years 5 months ago
Measured Descent: A New Embedding Method for Finite Metrics
We devise a new embedding technique, which we call measured descent, based on decomposing a metric space locally, at varying speeds, according to the density of some probability m...
Robert Krauthgamer, James R. Lee, Manor Mendel, As...
books