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JMLR
2010
134views more  JMLR 2010»
15 years 1 months ago
Inference of Graphical Causal Models: Representing the Meaningful Information of Probability Distributions
This paper studies the feasibility and interpretation of learning the causal structure from observational data with the principles behind the Kolmogorov Minimal Sufficient Statist...
Jan Lemeire, Kris Steenhaut
ICML
2007
IEEE
16 years 7 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
181
Voted
ICML
2008
IEEE
16 years 7 months ago
Gaussian process product models for nonparametric nonstationarity
Stationarity is often an unrealistic prior assumption for Gaussian process regression. One solution is to predefine an explicit nonstationary covariance function, but such covaria...
Ryan Prescott Adams, Oliver Stegle
ICML
2003
IEEE
16 years 7 months ago
Kernel PLS-SVC for Linear and Nonlinear Classification
A new method for classification is proposed. This is based on kernel orthonormalized partial least squares (PLS) dimensionality reduction of the original data space followed by a ...
Roman Rosipal, Leonard J. Trejo, Bryan Matthews
CHI
2003
ACM
16 years 6 months ago
Combined model for text entry rate development
We combine the power law of learning and theoretical upper limit predictions to describe the development of text entry rates from users' first contact to asymptotic expert us...
Poika Isokoski, I. Scott MacKenzie