Quantum-Inspired Magnetic Hamiltonian Monte Carlo.

Hamiltonian Monte Carlo (HMC) is a Markov Chain Monte Carlo algorithm that is able to generate distant proposals via the use of Hamiltonian dynamics, which are able to incorporate first-order gradient information about the target posterior. This has driven its rise in popularity in the machine learn...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Wilson Tsakane Mongwe, Rendani Mbuvha, Tshilidzi Marwala
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/2c718fa2e4cf4554bd9859532351e9ed
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:2c718fa2e4cf4554bd9859532351e9ed
record_format	dspace
spelling	oai:doaj.org-article:2c718fa2e4cf4554bd9859532351e9ed2021-12-02T20:13:48ZQuantum-Inspired Magnetic Hamiltonian Monte Carlo.1932-620310.1371/journal.pone.0258277https://doaj.org/article/2c718fa2e4cf4554bd9859532351e9ed2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0258277https://doaj.org/toc/1932-6203Hamiltonian Monte Carlo (HMC) is a Markov Chain Monte Carlo algorithm that is able to generate distant proposals via the use of Hamiltonian dynamics, which are able to incorporate first-order gradient information about the target posterior. This has driven its rise in popularity in the machine learning community in recent times. It has been shown that making use of the energy-time uncertainty relation from quantum mechanics, one can devise an extension to HMC by allowing the mass matrix to be random with a probability distribution instead of a fixed mass. Furthermore, Magnetic Hamiltonian Monte Carlo (MHMC) has been recently proposed as an extension to HMC and adds a magnetic field to HMC which results in non-canonical dynamics associated with the movement of a particle under a magnetic field. In this work, we utilise the non-canonical dynamics of MHMC while allowing the mass matrix to be random to create the Quantum-Inspired Magnetic Hamiltonian Monte Carlo (QIMHMC) algorithm, which is shown to converge to the correct steady state distribution. Empirical results on a broad class of target posterior distributions show that the proposed method produces better sampling performance than HMC, MHMC and HMC with a random mass matrix.Wilson Tsakane MongweRendani MbuvhaTshilidzi MarwalaPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 10, p e0258277 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Wilson Tsakane Mongwe Rendani Mbuvha Tshilidzi Marwala Quantum-Inspired Magnetic Hamiltonian Monte Carlo.
description	Hamiltonian Monte Carlo (HMC) is a Markov Chain Monte Carlo algorithm that is able to generate distant proposals via the use of Hamiltonian dynamics, which are able to incorporate first-order gradient information about the target posterior. This has driven its rise in popularity in the machine learning community in recent times. It has been shown that making use of the energy-time uncertainty relation from quantum mechanics, one can devise an extension to HMC by allowing the mass matrix to be random with a probability distribution instead of a fixed mass. Furthermore, Magnetic Hamiltonian Monte Carlo (MHMC) has been recently proposed as an extension to HMC and adds a magnetic field to HMC which results in non-canonical dynamics associated with the movement of a particle under a magnetic field. In this work, we utilise the non-canonical dynamics of MHMC while allowing the mass matrix to be random to create the Quantum-Inspired Magnetic Hamiltonian Monte Carlo (QIMHMC) algorithm, which is shown to converge to the correct steady state distribution. Empirical results on a broad class of target posterior distributions show that the proposed method produces better sampling performance than HMC, MHMC and HMC with a random mass matrix.
format	article
author	Wilson Tsakane Mongwe Rendani Mbuvha Tshilidzi Marwala
author_facet	Wilson Tsakane Mongwe Rendani Mbuvha Tshilidzi Marwala
author_sort	Wilson Tsakane Mongwe
title	Quantum-Inspired Magnetic Hamiltonian Monte Carlo.
title_short	Quantum-Inspired Magnetic Hamiltonian Monte Carlo.
title_full	Quantum-Inspired Magnetic Hamiltonian Monte Carlo.
title_fullStr	Quantum-Inspired Magnetic Hamiltonian Monte Carlo.
title_full_unstemmed	Quantum-Inspired Magnetic Hamiltonian Monte Carlo.
title_sort	quantum-inspired magnetic hamiltonian monte carlo.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/2c718fa2e4cf4554bd9859532351e9ed
work_keys_str_mv	AT wilsontsakanemongwe quantuminspiredmagnetichamiltonianmontecarlo AT rendanimbuvha quantuminspiredmagnetichamiltonianmontecarlo AT tshilidzimarwala quantuminspiredmagnetichamiltonianmontecarlo
_version_	1718374694912000000

Quantum-Inspired Magnetic Hamiltonian Monte Carlo.

Ejemplares similares