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Learning rates for the risk of kernel based quantile regression
  estimators in additive models

Learning rates for the risk of kernel based quantile regression estimators in additive models

14 May 2014
A. Christmann
Ding-Xuan Zhou
ArXiv (abs)PDFHTML

Papers citing "Learning rates for the risk of kernel based quantile regression estimators in additive models"

6 / 6 papers shown
Title
Generalized Sparse Additive Model with Unknown Link Function
Generalized Sparse Additive Model with Unknown Link Function
Peipei Yuan
Xinge You
Hao Chen
Xuelin Zhang
Qinmu Peng
185
0
0
08 Oct 2024
HARFE: Hard-Ridge Random Feature Expansion
HARFE: Hard-Ridge Random Feature Expansion
Esha Saha
Hayden Schaeffer
Giang Tran
147
15
0
06 Feb 2022
Total Stability of SVMs and Localized SVMs
Total Stability of SVMs and Localized SVMs
H. Köhler
A. Christmann
51
4
0
29 Jan 2021
Theory of Deep Convolutional Neural Networks II: Spherical Analysis
Theory of Deep Convolutional Neural Networks II: Spherical Analysis
Zhiying Fang
Han Feng
Shuo Huang
Ding-Xuan Zhou
112
38
0
28 Jul 2020
Generalized support vector regression: duality and tensor-kernel
  representation
Generalized support vector regression: duality and tensor-kernel representation
Saverio Salzo
Johan A. K. Suykens
67
8
0
18 Mar 2016
On the Robustness of Regularized Pairwise Learning Methods Based on
  Kernels
On the Robustness of Regularized Pairwise Learning Methods Based on Kernels
A. Christmann
Ding-Xuan Zhou
38
30
0
12 Oct 2015
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