Hawkes Processes Modeling, Inference and Control: An Overview
Machine Learning
2021-01-05 v2
Abstract
Hawkes Processes are a type of point process which models self-excitement among time events. It has been used in a myriad of applications, ranging from finance and earthquakes to crime rates and social network activity analysis.Recently, a surge of different tools and algorithms have showed their way up to top-tier Machine Learning conferences. This work aims to give a broad view of the recent advances on the Hawkes Processes modeling and inference to a newcomer to the field.
Cite
@article{arxiv.2011.13073,
title = {Hawkes Processes Modeling, Inference and Control: An Overview},
author = {Rafael Lima},
journal= {arXiv preprint arXiv:2011.13073},
year = {2021}
}
Comments
Fixed typos. Included pseudocodes for simulation algorithms. Improved figures. Included tables with complexity and performance comparisons. Included new sections on Current Challenges and Application Examples