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Risk Bounds for High-dimensional Ridge Function Combinations Including
  Neural Networks
v1v2v3v4 (latest)

Risk Bounds for High-dimensional Ridge Function Combinations Including Neural Networks

5 July 2016
Jason M. Klusowski
Andrew R. Barron
ArXiv (abs)PDFHTML

Papers citing "Risk Bounds for High-dimensional Ridge Function Combinations Including Neural Networks"

12 / 12 papers shown
Title
Universal approximation results for neural networks with non-polynomial activation function over non-compact domains
Universal approximation results for neural networks with non-polynomial activation function over non-compact domains
Ariel Neufeld
Philipp Schmocker
51
3
0
18 Oct 2024
Learning Combinations of Sigmoids Through Gradient Estimation
Learning Combinations of Sigmoids Through Gradient Estimation
Stratis Ioannidis
Andrea Montanari
30
2
0
22 Aug 2017
Recovery Guarantees for One-hidden-layer Neural Networks
Recovery Guarantees for One-hidden-layer Neural Networks
Kai Zhong
Zhao Song
Prateek Jain
Peter L. Bartlett
Inderjit S. Dhillon
MLT
175
337
0
10 Jun 2017
Minimax Lower Bounds for Ridge Combinations Including Neural Nets
Minimax Lower Bounds for Ridge Combinations Including Neural Nets
Jason M. Klusowski
Andrew R. Barron
77
22
0
09 Feb 2017
Learning Halfspaces and Neural Networks with Random Initialization
Learning Halfspaces and Neural Networks with Random Initialization
Yuchen Zhang
Jason D. Lee
Martin J. Wainwright
Michael I. Jordan
54
36
0
25 Nov 2015
$\ell_1$-regularized Neural Networks are Improperly Learnable in
  Polynomial Time
ℓ1\ell_1ℓ1​-regularized Neural Networks are Improperly Learnable in Polynomial Time
Yuchen Zhang
Jason D. Lee
Michael I. Jordan
186
103
0
13 Oct 2015
Learning by Transduction
Learning by Transduction
A. Gammerman
V. Vovk
V. Vapnik
186
515
0
30 Jan 2013
Tensor decompositions for learning latent variable models
Tensor decompositions for learning latent variable models
Anima Anandkumar
Rong Ge
Daniel J. Hsu
Sham Kakade
Matus Telgarsky
440
1,145
0
29 Oct 2012
Minimax rates of estimation for high-dimensional linear regression over
  $\ell_q$-balls
Minimax rates of estimation for high-dimensional linear regression over ℓq\ell_qℓq​-balls
Garvesh Raskutti
Martin J. Wainwright
Bin Yu
220
575
0
11 Oct 2009
Some sharp performance bounds for least squares regression with $L_1$
  regularization
Some sharp performance bounds for least squares regression with L1L_1L1​ regularization
Tong Zhang
136
270
0
20 Aug 2009
Approximation and learning by greedy algorithms
Approximation and learning by greedy algorithms
Andrew R. Barron
A. Cohen
W. Dahmen
Ronald A. DeVore
335
323
0
12 Mar 2008
Aggregation for Gaussian regression
Aggregation for Gaussian regression
F. Bunea
Alexandre B. Tsybakov
M. Wegkamp
507
362
0
19 Oct 2007
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