Optimal selection of sample-size dependent common subsets of covariates for multi-task regression prediction
From MaRDI portal
Publication:2074281
DOI10.1214/21-EJS1901zbMath1493.62456arXiv2012.05949OpenAlexW3196668636MaRDI QIDQ2074281
Publication date: 9 February 2022
Published in: Electronic Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2012.05949
model selectiontransfer learningoverfittingrandom covariatesequivalent number of observations (ENO)GENOMallows \(C_p\)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Bagging predictors
- User-friendly tail bounds for sums of random matrices
- Asymptotic properties of criteria for selection of variables in multiple regression
- Model assessment tools for a model false world
- Estimating the dimension of a model
- Adaptive covariate acquisition for minimizing total cost of classification
- Models as approximations. I. Consequences illustrated with linear regression
- Learning and equilibrium as useful approximations: accuracy of prediction on randomly selected constant sum games
- Probability and Stochastics
- From Fixed-X to Random-X Regression: Bias-Variance Decompositions, Covariance Penalties, and Prediction Error Estimation
- Can the strengths of AIC and BIC be shared? A conflict between model indentification and regression estimation
- A Tale of Two Regressions
- The Focused Information Criterion
- Model Selection and Multimodel Inference
- A note on the expected value of an inverse matrix
- Some Comments on C P
- Maximum Likelihood Estimation of Misspecified Models
- A new look at the statistical model identification