Learning Generalization and Regularization of Nonhomogeneous Temporal Poisson Processes

arXiv:2402.12808v1 Announce Type: new
Abstract: The Poisson process, especially the nonhomogeneous Poisson process (NHPP), is an essentially important counting process with numerous real-world applications. Up to date, almost all works in the literature have been on the estimation of NHPPs with infinite data using non-data driven binning methods. In this paper, we formulate the problem of estimation of NHPPs from finite and limited data as a learning generalization problem. We mathematically show that while binning methods are essential for the …

abstract applications arxiv cs.lg data literature paper process processes regularization stat.ml temporal type up to date world