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Improved Estimators for Semi-supervised High-dimensional Regression Model
We study a linear high-dimensional regression model in a semi-supervised...
02/14/2021 ∙ by Ilan Livne, et al. ∙
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Semiparametric Analysis of the Proportional Likelihood Ratio Model and Omnibus Estimation Procedure
We provide a semi-parametric analysis for the proportional likelihood ra...
06/03/2019 ∙ by Yair Goldberg, et al. ∙
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Hoeffding-Type and Bernstein-Type Inequalities for Right Censored Data
We present Hoeffding-type and Bernstein-type inequalities for right-cens...
03/05/2019 ∙ by Yair Goldberg, et al. ∙
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Kernel Machines With Missing Responses
Missing responses is a missing data format in which outcomes are not alw...
06/07/2018 ∙ by Tiantian Liu, et al. ∙
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Self-reporting and screening: Data with current-status and censored observations
We consider survival data that combine three types of observations: unce...
03/06/2018 ∙ by Jonathan Yefenof, et al. ∙
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Support Vector Machines for Current Status Data
Current status data is a data format where the time to event is restrict...
05/05/2015 ∙ by Yael Travis-Lumer, et al. ∙
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Feature Elimination in Kernel Machines in moderately high dimensions
We develop an approach for feature elimination in statistical learning w...
04/18/2013 ∙ by Sayan Dasgupta, et al. ∙
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Support Vector Regression for Right Censored Data
We develop a unified approach for classification and regression support ...
02/23/2012 ∙ by Yair Goldberg, et al. ∙
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LLE with low-dimensional neighborhood representation
The local linear embedding algorithm (LLE) is a non-linear dimension-red...
08/06/2008 ∙ by Yair Goldberg, et al. ∙
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