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ICML
2007
IEEE
15 years 6 hour ago
Asymptotic Bayesian generalization error when training and test distributions are different
In supervised learning, we commonly assume that training and test data are sampled from the same distribution. However, this assumption can be violated in practice and then standa...
Keisuke Yamazaki, Klaus-Robert Müller, Masash...
BMCBI
2006
110views more  BMCBI 2006»
13 years 11 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
ICANN
2005
Springer
14 years 4 months ago
Some Issues About the Generalization of Neural Networks for Time Series Prediction
Abstract. Some issues about the generalization of ANN training are investigated through experiments with several synthetic time series and real world time series. One commonly acce...
Wen Wang, Pieter H. A. J. M. van Gelder, J. K. Vri...
TSP
2008
115views more  TSP 2008»
13 years 11 months ago
A Bayesian Approach to Adaptive Detection in Nonhomogeneous Environments
Abstract--We consider the adaptive detection of a signal of interest embedded in colored noise, when the environment is nonhomogeneous, i.e., when the training samples used for ada...
Stéphanie Bidon, Olivier Besson, Jean-Yves ...
NAACL
2010
13 years 9 months ago
Training Paradigms for Correcting Errors in Grammar and Usage
This paper proposes a novel approach to the problem of training classifiers to detect and correct grammar and usage errors in text by selectively introducing mistakes into the tra...
Alla Rozovskaya, Dan Roth