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Robust high dimensional learning for Lipschitz and convex losses

Robust high dimensional learning for Lipschitz and convex losses

10 May 2019
Geoffrey Chinot
Guillaume Lecué
M. Lerasle
ArXivPDFHTML

Papers citing "Robust high dimensional learning for Lipschitz and convex losses"

4 / 4 papers shown
Title
A Unified Analysis of Multi-task Functional Linear Regression Models
  with Manifold Constraint and Composite Quadratic Penalty
A Unified Analysis of Multi-task Functional Linear Regression Models with Manifold Constraint and Composite Quadratic Penalty
Shiyuan He
Hanxuan Ye
Kejun He
11
0
0
09 Nov 2022
Outlier Robust and Sparse Estimation of Linear Regression Coefficients
Outlier Robust and Sparse Estimation of Linear Regression Coefficients
Takeyuki Sasai
Hironori Fujisawa
22
4
0
24 Aug 2022
Universal Robust Regression via Maximum Mean Discrepancy
Universal Robust Regression via Maximum Mean Discrepancy
Pierre Alquier
Mathieu Gerber
32
15
0
01 Jun 2020
Learning without Concentration
Learning without Concentration
S. Mendelson
80
333
0
01 Jan 2014
1