Non-asymptotic bounds for prediction problems and density estimation.
This dissertation investigates the learning scenarios where a high-dimensional parameter has to be estimated from a given sample of fixed size, often smaller than the dimension of the problem. The first part answers some open questions for the binary classification problem in the framework of active...
Main Author: | Minsker, Stanislav |
---|---|
Published: |
Georgia Institute of Technology
2012
|
Subjects: | |
Online Access: | http://hdl.handle.net/1853/44808 |
Similar Items
-
Contributions to the asymptotic theory of estimation and hypothesis testing when the model is incorrect.
by: Teoh, Kok Wah
Published: (1981) -
Limiting distributions of maximum probability estimators of nonstationary autoregressive processes.
Published: (2002) -
Uses of Bayesian posterior modes in solving complex estimation problems in statistics
by: Lin, Lie-fen
Published: (2013) -
A data-driven bandwidth selector for estimating conditional density function.
Published: (2003) -
Asymptotic expansions of empirical likelihood in time series.
Published: (2009)