65 citations · 82 across the 14 of their papers we have counts for
16 papers
Hold-out estimates of prediction models for Markov processes
Remy Garnier, Raphaël Langhendries, Joseph Rynkiewicz
We consider the selection of prediction models for Markovian time series. For this purpose, we study the theoretical properties of the hold-out method. In the econometrics literatu…
Spectral estimation for non-linear long range dependent discrete time trawl processes
Paul Doukhan, François Roueff, Joseph Rynkiewicz
Discrete time trawl processes constitute a large class of time series parameterized by a trawl sequence (a j) jN and defined though a sequence of independent and identically d…
Asymptotics for regression models under loss of identifiability
Joseph Rynkiewicz
This paper discusses the asymptotic behavior of regression models under general conditions. First, we give a general inequality for the difference of the sum of square errors (SSE)…
Neural Networks for Complex Data
Marie Cottrell, Madalina Olteanu, Fabrice Rossi +2
Artificial neural networks are simple and efficient machine learning tools. Defined originally in the traditional setting of simple vector data, neural network models have evolved…
General bound of overfitting for MLP regression models
Joseph Rynkiewicz
Multilayer perceptrons (MLP) with one hidden layer have been used for a long time to deal with non-linear regression. However, in some task, MLP's are too powerful models and a sma…
Asymptotic law of likelihood ratio for multilayer perceptron models
Joseph Rynkiewicz
We consider regression models involving multilayer perceptrons (MLP) with one hidden layer and a Gaussian noise. The data are assumed to be generated by a true MLP model and the es…