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ICASSP
2011
IEEE
14 years 8 months ago
On selecting the hyperparameters of the DPM models for the density estimation of observation errors
The Dirichlet Process Mixture (DPM) models represent an attractive approach to modeling latent distributions parametrically. In DPM models the Dirichlet process (DP) is applied es...
Asma Rabaoui, Nicolas Viandier, Juliette Marais, E...
132
Voted
BMCBI
2006
110views more  BMCBI 2006»
15 years 4 months ago
Bias in error estimation when using cross-validation for model selection
Background: Cross-validation (CV) is an effective method for estimating the prediction error of a classifier. Some recent articles have proposed methods for optimizing classifiers...
Sudhir Varma, Richard Simon
115
Voted
CI
2002
92views more  CI 2002»
15 years 4 months ago
Model Selection in an Information Economy: Choosing What to Learn
As online markets for the exchange of goods and services become more common, the study of markets composed at least in part of autonomous agents has taken on increasing importance...
Christopher H. Brooks, Robert S. Gazzale, Rajarshi...
ICPR
2006
IEEE
15 years 10 months ago
Real Time Limb Tracking with Adaptive Model Selection
We describe an efficient and robust method of tracking human forearms as skin colored regions. Of special consideration in the design of this system are real-time and robustness ...
Matheen Siddiqui, Gérard G. Medioni
GECCO
2008
Springer
192views Optimization» more  GECCO 2008»
15 years 5 months ago
Non-linear factor model for asset selection using multi objective genetic programming
Investors vary with respect to their expected return and aversion to associated risk, and hence also vary in their performance expectations of the stock market portfolios they hol...
Ghada Hassan