4 papers
Subsampling for supervised learning in reproducing kernel Hilbert spaces
Eyal Vayness, Maxime Sangnier
In the era of big data, subsampling became a common practice in statistical learning. By selecting a subgroup of individuals based on which the learner is trained, subsampling aims…
Hawkes Processes with Variable Length Memory: Existence, Inference and Application to Neuronal Activity
Sacha Quayle, Anna Bonnet, Maxime Sangnier
Multivariate Hawkes processes are past-dependant point processes originally introduced to model excitation effects, later extended to a nonlinear framework to account for the oppos…
Spectral analysis for the inference of noisy Hawkes processes
Anna Bonnet, Felix Cheysson, Miguel Martinez Herrera +1
Classic estimation methods for Hawkes processes rely on the assumption that observed event times are indeed a realisation of a Hawkes process, without considering any potential per…
Nonparametric estimation of Hawkes processes with RKHSs
Anna Bonnet, Maxime Sangnier
This paper addresses nonparametric estimation of nonlinear multivariate Hawkes processes, where the interaction functions are assumed to lie in a reproducing kernel Hilbert space (…