Learning Single Index Models in High Dimensions

Semiparametric least squares (sls) and weighted sls estimation of single-index models

Hidehiko Ichimura · 1993

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Direct semiparametric estimation of single-index models with discrete covariates

Joel L Horowitz and Wolfgang Härdle · 1996

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Using unlabeled data to improve text classification

Kamal Paul Nigam · 2001

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Covering number bounds of certain regularized linear function classes

Tong Zhang · 2002

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L1-regularization path algorithm for generalized linear models

Mee Young Park and Trevor Hastie · 2007

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High-dimensional generalized linear models and the lasso

Sara A Van de Geer · 2008

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Semiparametric and nonparametric methods in econometrics

Joel L Horowitz · 2009

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The isotron algorithm: High-dimensional isotonic regression

Adam Tauman Kalai and Ravi Sastry · 2009

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Optimization methods for l1-regularization

Mark Schmidt, Glenn Fung, and Romer Rosales · 2009

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Smoothness, low noise and fast rates

Nathan Srebro, Karthik Sridharan, and Ambuj Tewari · 2010

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Efficient learning of generalized linear and single index models with isotonic regression

Sham M Kakade, Varun Kanade, Ohad Shamir, and Adam Kalai · 2011

Cited alongside, same era.

A unified framework for high-dimensional analysis of m-estimators with decomposable regularizers

Sahand N Negahban, Pradeep Ravikumar, Martin J Wainwright, and Bin Yu · 2012

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Sparse single-index model

Pierre Alquier and Gérard Biau · 2013

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Robust 1-bit compressed sensing and sparse logistic regression: A convex programming approach

Yaniv Plan and Roman Vershynin · 2013

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High-dimensional estimation with geometric constraints

Original

Yaniv Plan, Roman Vershynin, and Elena Yudovina · 2014

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Classification with sparse overlapping groups

Original

Nikhil S Rao, Robert D Nowak, Christopher R Cox, and Timothy T Rogers · 2014

Later among the works it cites.