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SIGPRO
2011
275views Hardware» more  SIGPRO 2011»
13 years 3 months ago
Synthesis of multivariate stationary series with prescribed marginal distributions and covariance using circulant matrix embeddi
The problem of synthesizing multivariate stationary series Y [n] = (Y1[n], . . . , YP [n])T , n ∈ Z, with prescribed non-Gaussian marginal distributions, and a targeted covarian...
Hannes Helgason, Vladas Pipiras, Patrice Abry
JMLR
2010
101views more  JMLR 2010»
13 years 7 months ago
Exploiting Feature Covariance in High-Dimensional Online Learning
Some online algorithms for linear classification model the uncertainty in their weights over the course of learning. Modeling the full covariance structure of the weights can prov...
Justin Ma, Alex Kulesza, Mark Dredze, Koby Crammer...
JMLR
2010
169views more  JMLR 2010»
13 years 7 months ago
Factored 3-Way Restricted Boltzmann Machines For Modeling Natural Images
Deep belief nets have been successful in modeling handwritten characters, but it has proved more difficult to apply them to real images. The problem lies in the restricted Boltzma...
Marc'Aurelio Ranzato, Alex Krizhevsky, Geoffrey E....
CSDA
2006
84views more  CSDA 2006»
14 years 14 days ago
Performing hypothesis tests on the shape of functional data
We explore different approaches for performing hypothesis tests on the shape of a mean function by developing general methodologies both, for the often assumed, i.i.d. error struc...
Gareth M. James, Ashish Sood
HICSS
2003
IEEE
180views Biometrics» more  HICSS 2003»
14 years 5 months ago
Impact of Electronic Commerce Customer Relationship Management on Corporate Success - Results from an Empirical Investigation
In this contribution, we study companies engaging in B2C-E-Commerce and their ability to manage the relationship with their customers. We refer to this as companies’ ECCRM-capab...
Nils Madeja, Detlef Schoder
ICML
2007
IEEE
15 years 1 months ago
Modeling changing dependency structure in multivariate time series
We show how to apply the efficient Bayesian changepoint detection techniques of Fearnhead in the multivariate setting. We model the joint density of vector-valued observations usi...
Xiang Xuan, Kevin P. Murphy