The KL generalization error in unsupervised learning decomposes exactly into model error, data bias, and variance for e-flat models, with closed-form results for ε-PCA on isotropic Gaussians showing optimal rank at the noise floor and a three-regime phase diagram.
Asymptotic equivalence of Bayes cross validation and widely applicable information criterion in singular learning theory.Journal of Machine Learning Research, 11:3571–3594, 2010
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ML 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Information-Geometric Decomposition of Generalization Error in Unsupervised Learning
The KL generalization error in unsupervised learning decomposes exactly into model error, data bias, and variance for e-flat models, with closed-form results for ε-PCA on isotropic Gaussians showing optimal rank at the noise floor and a three-regime phase diagram.