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An Adversarial Approach to Structural Estimation

An Adversarial Approach to Structural Estimation

13 July 2020
Tetsuya Kaji
E. Manresa
G. Pouliot
ArXivPDFHTML

Papers citing "An Adversarial Approach to Structural Estimation"

18 / 18 papers shown
Title
Pre-Training Estimators for Structural Models: Application to Consumer Search
Pre-Training Estimators for Structural Models: Application to Consumer Search
Yanhao 'Max' Wei
Zhenling Jiang
121
0
0
01 May 2025
Function approximation by deep networks
Function approximation by deep networks
H. Mhaskar
T. Poggio
65
23
0
30 May 2019
Deep Generalized Method of Moments for Instrumental Variable Analysis
Deep Generalized Method of Moments for Instrumental Variable Analysis
Andrew Bennett
Nathan Kallus
Tobias Schnabel
57
128
0
29 May 2019
How Well Generative Adversarial Networks Learn Distributions
How Well Generative Adversarial Networks Learn Distributions
Tengyuan Liang
GAN
46
95
0
07 Nov 2018
Deep Neural Networks for Estimation and Inference
Deep Neural Networks for Estimation and Inference
M. Farrell
Tengyuan Liang
S. Misra
BDL
160
254
0
26 Sep 2018
Adversarial Generalized Method of Moments
Adversarial Generalized Method of Moments
Greg Lewis
Vasilis Syrgkanis
GAN
30
59
0
19 Mar 2018
Orthogonal Machine Learning: Power and Limitations
Orthogonal Machine Learning: Power and Limitations
Lester W. Mackey
Vasilis Syrgkanis
Ilias Zadik
130
42
0
01 Nov 2017
Nonparametric regression using deep neural networks with ReLU activation
  function
Nonparametric regression using deep neural networks with ReLU activation function
Johannes Schmidt-Hieber
214
810
0
22 Aug 2017
Indirect Inference with a Non-Smooth Criterion Function
Indirect Inference with a Non-Smooth Criterion Function
David T. Frazier
Tatsushi Oka
Dan Zhu
40
11
0
08 Aug 2017
Nearly-tight VC-dimension and pseudodimension bounds for piecewise
  linear neural networks
Nearly-tight VC-dimension and pseudodimension bounds for piecewise linear neural networks
Peter L. Bartlett
Nick Harvey
Christopher Liaw
Abbas Mehrabian
195
431
0
08 Mar 2017
Towards Principled Methods for Training Generative Adversarial Networks
Towards Principled Methods for Training Generative Adversarial Networks
Martín Arjovsky
M. Nault
GAN
79
2,106
0
17 Jan 2017
Error bounds for approximations with deep ReLU networks
Error bounds for approximations with deep ReLU networks
Dmitry Yarotsky
187
1,226
0
03 Oct 2016
f-GAN: Training Generative Neural Samplers using Variational Divergence
  Minimization
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization
Sebastian Nowozin
Botond Cseke
Ryota Tomioka
GAN
137
1,654
0
02 Jun 2016
Generalized Indirect Inference for Discrete Choice Models
Generalized Indirect Inference for Discrete Choice Models
M. Bruins
James A. Duffy
M. Keane
Anthony Smith
36
58
0
22 Jul 2015
Breaking the Curse of Dimensionality with Convex Neural Networks
Breaking the Curse of Dimensionality with Convex Neural Networks
Francis R. Bach
174
706
0
30 Dec 2014
Convergence of linear functionals of the Grenander estimator under
  misspecification
Convergence of linear functionals of the Grenander estimator under misspecification
H. Jankowski
79
32
0
27 Jul 2012
A local maximal inequality under uniform entropy
A local maximal inequality under uniform entropy
A. van der Vaart
J. Wellner
85
80
0
26 Dec 2010
Efficient Simulation-Based Minimum Distance Estimation and Indirect
  Inference
Efficient Simulation-Based Minimum Distance Estimation and Indirect Inference
Richard Nickl
B. M. Potscher
113
15
0
04 Aug 2009
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