@inproceedings{9f4625b0605a4afe98ab724acb42ef46,
title = "Laplacian Hamiltonian Monte Carlo",
abstract = "We proposed a Hamiltonian Monte Carlo (HMC) method with Laplace kinetic energy, and demonstrate the connection between slice sampling and proposed HMC method in one-dimensional cases. Based on this connection, one can perform slice sampling using a numerical integrator in an HMC fashion. We provide theoretical analysis on the performance of such sampler in several univariate cases. Furthermore, the proposed approach extends the standard HMC by enabling sampling from discrete distributions. We compared our method with standard HMC on both synthetic and real data, and discuss its limitations and potential improvements.",
author = "Yizhe Zhang and Changyou Chen and Ricardo Henao and Lawrence Carin",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.; 15th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2016 ; Conference date: 19-09-2016 Through 23-09-2016",
year = "2016",
doi = "10.1007/978-3-319-46128-1\_7",
language = "English",
isbn = "9783319461274",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "98--114",
editor = "Jilles Giuseppe and Niels Landwehr and Giuseppe Manco and Paolo Frasconi",
booktitle = "Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2016, Proceedings",
address = "Germany",
}