Sparse high-dimensional isotonic regression
© 2019 Neural information processing systems foundation. All rights reserved. We consider the problem of estimating an unknown coordinate-wise monotone function given noisy measurements, known as the isotonic regression problem. Often, only a small subset of the features affects the output. This mot...
Main Authors: | Gamarnik, David, Gaudio, Julia |
---|---|
Format: | Article |
Language: | English |
Published: |
2021
|
Online Access: | https://hdl.handle.net/1721.1/137482 |
Similar Items
-
Sparse high-dimensional isotonic regression
by: Gamarnik, David, et al.
Published: (2021) -
LASSO ISOtone for High Dimensional Additive Isotonic Regression
by: Fang, Z, et al.
Published: (2010) -
Sparse high-dimensional linear regression. Estimating squared error and a phase transition
by: Gamarnik, David, et al.
Published: (2022) -
Uncoupled isotonic regression via minimum Wasserstein deconvolution
by: Rigollet, Philippe, et al.
Published: (2020) -
Statistical inference under order restrictions : the isotonic regression /
by: Barlow, R. E.
Published: (1972)