3 papers
math.ST2025
Frontiers to the learning of nonparametric hidden Markov models
Kweku Abraham, Elisabeth Gassiat, Zacharie Naulet
Hidden Markov models (HMMs) are flexible tools for clustering dependent data coming from unknown populations, allowing nonparametric modelling of the population densities. Identifi…
math.ST2024
Deconvolution of repeated measurements corrupted by unknown noise
Jérémie Capitao-Miniconi, Elisabeth Gassiat, Luc Lehéricy
Recent advances have demonstrated the possibility of solving the deconvolution problem without prior knowledge of the noise distribution. In this paper, we study the repeated measu…
math.ST2024
Support and distribution inference from noisy data
Jérémie Capitao-Miniconi, Elisabeth Gassiat, Luc Lehéricy
We consider noisy observations of a distribution with unknown support. In the deconvolution model, it has been proved recently [19] that, under very mild assumptions, it is possibl…