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ICCV
2003
IEEE
14 years 12 months ago
Controlling Model Complexity in Flow Estimation
This paper describes a novel application of Statistical Learning Theory (SLT) to control model complexity in flow estimation. SLT provides analytical generalization bounds suitabl...
Zoran Duric, Fayin Li, Harry Wechsler, Vladimir Ch...
ICIP
2005
IEEE
14 years 11 months ago
Custom color enhancements by statistical learning
We consider the problem of automatically learning color enhancements from a small set of sample color pairs, and describing the enhancement by a three-dimensional look-uptable tha...
Maya R. Gupta
ICML
2009
IEEE
14 years 10 months ago
The Bayesian group-Lasso for analyzing contingency tables
Group-Lasso estimators, useful in many applications, suffer from lack of meaningful variance estimates for regression coefficients. To overcome such problems, we propose a full Ba...
Sudhir Raman, Thomas J. Fuchs, Peter J. Wild, Edga...
ICML
2008
IEEE
14 years 10 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
2006
IEEE
14 years 10 months ago
Dynamic topic models
A family of probabilistic time series models is developed to analyze the time evolution of topics in large document collections. The approach is to use state space models on the n...
David M. Blei, John D. Lafferty