130 citations · 314 across the 29 of their papers we have counts for
24 papers · 1 filter
Estimation in linear high dimensional Hawkes processes: a Bayesian approach
Judith Rousseau, Vincent Rivoirard, Déborah Sulem
In this paper we study the frequentist properties of Bayesian approaches in linear high dimensional Hawkes processes in a sparse regime where the number of interaction functions ac…
Is model selection possible for the -loss? PCO estimation for regression models
Claire Lacour, Pascal Massart, Vincent Rivoirard
This paper addresses the problem of model selection in the sequence model , when is sub-Gaussian, for non-euclidian loss-functions. In this model, the Penaliz…
Scalable and adaptive variational Bayes methods for Hawkes processes
Deborah Sulem, Vincent Rivoirard, Judith Rousseau
Hawkes processes are often applied to model dependence and interaction phenomena in multivariate event data sets, such as neuronal spike trains, social interactions, and financial…
Adaptive warped kernel estimation for nonparametric regression with circular responses
Tien Dat Nguyen, Thanh Mai Pham Ngoc, Vincent Rivoirard
In this paper, we deal with nonparametric regression for circular data, meaning that observations are represented by points lying on the unit circle. We propose a kernel estimation…
Adaptive greedy algorithm for moderately large dimensions in kernel conditional density estimation
Minh-Lien Jeanne Nguyen, Claire Lacour, Vincent Rivoirard
This paper studies the estimation of the conditional density f (x, ) of Y i given X i = x, from the observation of an i.i.d. sample (X i , Y i) R d , i = 1,. .. , n.…
Bayesian estimation of nonlinear Hawkes process
Deborah Sulem, Vincent Rivoirard, Judith Rousseau
Multivariate point processes are widely applied to model event-type data such as natural disasters, online message exchanges, financial transactions or neuronal spike trains. One v…