Kernel machines with missing covariates
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Publication:6184885
DOI10.1214/23-ejs2158OpenAlexW4388202653MaRDI QIDQ6184885
Publication date: 5 January 2024
Published in: Electronic Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://projecteuclid.org/journals/electronic-journal-of-statistics/volume-17/issue-2/Kernel-machines-with-missing-covariates/10.1214/23-EJS2158.full
Nonparametric regression and quantile regression (62G08) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Sampling theory, sample surveys (62D05) Learning and adaptive systems in artificial intelligence (68T05)
Cites Work
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- Kernel methods in machine learning
- Fast rates for support vector machines using Gaussian kernels
- Introduction to double robust methods for incomplete data
- Kernel machines with missing responses
- Introduction to empirical processes and semiparametric inference
- Semiparametric theory and missing data.
- Handling missing values in support vector machine classifiers
- Sampling Statistics
- Support Vector Machines
- Estimation of Regression Coefficients When Some Regressors Are Not Always Observed
- Order-Preserving Nonparametric Regression, With Applications to Conditional Distribution and Quantile Function Estimation
- Adjusting for Nonignorable Drop-Out Using Semiparametric Nonresponse Models
- Estimating Individualized Treatment Rules Using Outcome Weighted Learning
- A General Framework for Quantile Estimation with Incomplete Data
- Doubly robust learning for estimating individualized treatment with censored data
- Convexity, Classification, and Risk Bounds
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