Noise contrastive estimation: asymptotic properties, formal comparison with MC-MLE
type: Item
instance of: scholarly article
title: Noise contrastive estimation: asymptotic properties, formal comparison with MC-MLE
zbMATH Open document ID: 1407.62069
DOI: 10.1214/18-EJS1485
author: Lionel Riou-Durand
author: Nicolas Chopin
published in: Electronic Journal of Statistics
publication date: 2018-11-01T00:00:00Z
full work available at URL: https://arxiv.org/abs/1801.10381
full work available at URL: https://projecteuclid.org/euclid.ejs/1539741651
Mathematics Subject Classification ID: 62F10
Mathematics Subject Classification ID: 65C05
zbMATH DE Number: 6970010
MaRDI profile type: Publication
arXiv ID: 1801.10381
cites work: Concavity of certain maps on positive definite matrices and applications to Hadamard products
cites work: The Poisson transform for unnormalised statistical models
cites work: Q4821526
cites work: Basic properties of strong mixing conditions. A survey and some open questions
cites work: Q4280431
cites work: Maximum likelihood estimation for spatial models by Markov chain Monte Carlo stochastic approximation
cites work: Q5405118
cites work: On the Markov chain central limit theorem
cites work: Markov chains and stochastic stability
cites work: General state space Markov chains and MCMC algorithms
cites work: Variational Analysis
cites work: An efficient learning procedure for deep Boltzmann machines
cites work: Note on the Consistency of the Maximum Likelihood Estimate
cites work: Posterior Sampling When the Normalizing Constant is Unknown
OpenAlex ID: W2897723259
description: scientific article