Sciweavers

273 search results - page 1 / 55
» Estimation of prediction error by using K-fold cross-validat...
Sort
View
ICML
1994
IEEE
13 years 8 months ago
Efficient Algorithms for Minimizing Cross Validation Error
Model selection is important in many areas of supervised learning. Given a dataset and a set of models for predicting with that dataset, we must choose the model which is expected...
Andrew W. Moore, Mary S. Lee
NECO
2002
145views more  NECO 2002»
13 years 4 months ago
Bayesian Model Assessment and Comparison Using Cross-Validation Predictive Densities
In this work, we discuss practical methods for the assessment, comparison, and selection of complex hierarchical Bayesian models. A natural way to assess the goodness of the model...
Aki Vehtari, Jouko Lampinen
COLT
1999
Springer
13 years 8 months ago
Beating the Hold-Out: Bounds for K-fold and Progressive Cross-Validation
The empirical error on a test set, the hold-out estimate, often is a more reliable estimate of generalization error than the observed error on the training set, the training estim...
Avrim Blum, Adam Kalai, John Langford
IROS
2008
IEEE
173views Robotics» more  IROS 2008»
13 years 11 months ago
Automatically smoothing camera pose using cross validation for sequential vision-based 3D mapping
— Building an accurate three dimensional map is an important task for autonomous localisation and navigation. In a sequential approach to reconstruction from video streams, we sh...
Michela Farenzena, Adrien Bartoli, Youcef Mezouar
ECCV
2008
Springer
14 years 6 months ago
Efficient Camera Smoothing in Sequential Structure-from-Motion Using Approximate Cross-Validation
Abstract. In the sequential approach to three-dimensional reconstruction, adding prior knowledge about camera pose improves reconstruction accuracy. We add a smoothing penalty on t...
Michela Farenzena, Adrien Bartoli, Youcef Mezouar