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Direct coupling information measure from non-uniform embedding
Direct coupling information measure non-uniform embedding
2013/6/17
A measure to estimate the direct and directional coupling in multivariate time series is proposed. The measure is an extension of a recently published measure of conditional Mutual Information from Mi...
Embedding Riemannian Manifolds by the Heat Kernel of the Connection Laplacian
Embedding Riemannian Manifolds Heat Kernel Connection Laplacian
2013/6/17
Given a class of closed Riemannian manifolds with prescribed geometric conditions, we introduce an embedding of the manifolds into $\ell^2$ based on the heat kernel of the Connection Laplacian associa...
Path Integral Control by Reproducing Kernel Hilbert Space Embedding
Path Integral Control Reproducing Kernel Hilbert Space Embedding
2012/9/18
We present an embedding of stochastic optimal control problems, of the so called path integral form, into reproducing kernel Hilbert spaces. Using consistent, sample based estimates of the embedding l...
Manifold embedding for curve registration
Manifold learning Intrinsic statistics Structural statistics Graph-based methods Curve alignment Curve registration Warping Model Functional data
2011/6/20
We focus on the problem of finding a good representative of a
sample of random curves warped from a common pattern f. We first
prove that such a problem can be moved onto a manifold framework.
Then...
Universality,Characteristic Kernels and RKHS Embedding of Measures
Kernel methods Characteristic kernels Hilbert space embeddings Universalkernels Translation invariant kernels Radial kernels
2010/3/11
A Hilbert space embedding for probability measures has recently been proposed, wherein
any probability measure is represented as a mean element in a reproducing kernel Hilbert
space (RKHS). Such an ...
The Skorokhod embedding problem and its offspring
Skorokhod embedding problem Chacon-Walsh embedding Azéma-Yor embedding Root embedding stopping times
2009/5/18
This is a survey about the Skorokhod embedding problem. It presents all known solutions together with their properties and some applications. Some of the solutions are just described, while others are...
Metric Embedding for Nearest Neighbor Classification
Metric Embedding Nearest Neighbor Classification
2010/4/29
The distance metric plays an important role in nearest neighbor (NN) classification. Usually
the Euclidean distance metric is assumed or a Mahalanobis distance metric is optimized
to improve the NN ...