Inverse statistical learning
From MaRDI portal
Publication:364201
DOI10.1214/13-EJS838zbMath1349.62102MaRDI QIDQ364201
Publication date: 6 September 2013
Published in: Electronic Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://projecteuclid.org/euclid.ejs/1377005820
Classification and discrimination; cluster analysis (statistical aspects) (62H30) Nonparametric estimation (62G05)
Related Items (3)
Noisy discriminant analysis with boundary assumptions ⋮ Optimal rates for regularization of statistical inverse learning problems ⋮ Bandwidth selection in kernel empirical risk minimization via the gradient
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- General nonexact oracle inequalities for classes with a subexponential envelope
- New concentration inequalities for suprema of empirical processes
- On the optimal rates of convergence for nonparametric deconvolution problems
- Risk bounds for statistical learning
- Deconvolution problems in nonparametric statistics
- Fast learning rates for plug-in classifiers
- Estimation of dependences based on empirical data. Transl. from the Russian by Samuel Kotz
- Smooth discrimination analysis
- A Bennett concentration inequality and its application to suprema of empirical processes
- Optimal aggregation of classifiers in statistical learning.
- Measuring mass concentrations and estimating density contour clusters -- An excess mass approach
- Weak convergence and empirical processes. With applications to statistics
- Penalized empirical risk minimization over Besov spaces
- Minimax fast rates for discriminant analysis with errors in variables
- Local Rademacher complexities and oracle inequalities in risk minimization. (2004 IMS Medallion Lecture). (With discussions and rejoinder)
- Statistical performance of support vector machines
- On deconvolution with repeated measurements
- Goodness-of-fit testing and quadratic functional estimation from indirect observations
- Empirical minimization
- Square root penalty: Adaption to the margin in classification and in edge estimation
- Local Rademacher complexities
- Nonparametric statistical inverse problems
- Generalization performance of regularization networks and support vector machines via entropy numbers of compact operators
- Some applications of concentration inequalities to statistics
- New concentration inequalities in product spaces
This page was built for publication: Inverse statistical learning
