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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...
Dynamics of Snoring Sounds and Its Connection with Obstructive Sleep Apnea
snore Hurst time interval OSA
2012/9/18
Snoring is extremely common in the general population and when irregu-lar may indicate the presence of obstructive sleep apnea. We analyze the overnight sequence of wave packets | the snore sound | re...
Vector Diffusion Maps and the Connection Laplacian
Dimensionality reduction vector elds heat kernel parallel transport local prin-cipal component analysis alignment
2011/3/18
Abstract. We introduce vector di usion maps (VDM), a new mathematical framework for orga-nizing and analyzing massive high dimensional data sets, images and shapes. VDM is a mathematical and algorithm...
This paper describes a qualitative study investigating the work environment necessary for virtual teams to be creative. Nine virtual teams, with a total of 36 team members participated. One semi-struc...
A connection between the stochastic heat equation and fractional Brownian motion, and a simple proof of a result of Talagrand
heat equation white noise stochastic partial differential equations
2009/4/29
We give a new representation of fractional Brownian motion with Hurst parameter $Hleqfrac{1}{2}$ using stochastic partial differential equations. This representation allows us to use the Markov proper...
A connection between the stochastic heat equation and fractional Brownian motion, and a simple proof of a result of Talagrand
stochastic fractional Brownian motion
2009/4/22
We give a new representation of fractional Brownian motion with Hurst parameter $Hleqfrac{1}{2}$ using stochastic partial differential equations. This representation allows us to use the Markov proper...
ON THE CONNECTION BETWEEN THE DISTRIBUTION OF EIGENVALUES IN MULTIPLE CORRESPONDENCE ANALYSIS AND LOG-LINEAR MODELS
Multiple Correspondence Analysis eigenvalues log-linear models graphical models normal distribution
2009/2/26
Multiple Correspondence Analysis (MCA) and log-linear modeling are two techniques for multi-way contingency table analysis having di®erent approaches and ¯elds of applications. Log-linear mod...