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An Efficient Relaxed Projection Method for Constrained Non-negative Matrix Factorization with Application to the Phase-Mapping Problem in Materials Science

Bai, Junwen and Ament, Sebastian and Perez, Guillaume and Gregoire, John and Gomes, Carla (2018) An Efficient Relaxed Projection Method for Constrained Non-negative Matrix Factorization with Application to the Phase-Mapping Problem in Materials Science. In: Integration of Constraint Programming, Artificial Intelligence, and Operations Research. Lecture Notes in Computer Science. No.10848. Springer , Cham, Switzerland, pp. 52-62. ISBN 978-3-319-93030-5. https://resolver.caltech.edu/CaltechAUTHORS:20180607-155251991

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Abstract

In recent years, a number of methods for solving the constrained non-negative matrix factorization problem have been proposed. In this paper, we propose an efficient method for tackling the ever increasing size of real-world problems. To this end, we propose a general relaxation and several algorithms for enforcing constraints in a challenging application: the phase-mapping problem in materials science. Using experimental data we show that the proposed method significantly outperforms previous methods in terms of ℓ_2-norm error and speed.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1007/978-3-319-93031-2_4DOIArticle
https://rdcu.be/UrGhPublisherFree ReadCube access
ORCID:
AuthorORCID
Gregoire, John0000-0002-2863-5265
Additional Information:© 2018 Springer International Publishing AG, part of Springer Nature. First Online: 08 June 2018. Work supported by an NSF Expedition award for Computational Sustainability (CCF-1522054), NSF Computing Research Infrastructure (CNS-1059284), NSF Inspire (1344201), a MURI/AFOSR grant (FA9550), and a grant from the Toyota Research Institute.
Group:JCAP
Funders:
Funding AgencyGrant Number
NSFCCF-1522054
NSFCNS-1059284
NSFCNS-1059284
NSFIIS-1344201
Air Force Office of Scientific Research (AFOSR)FA9550
Toyota Research InstituteUNSPECIFIED
Series Name:Lecture Notes in Computer Science
Issue or Number:10848
DOI:10.1007/978-3-319-93031-2_4
Record Number:CaltechAUTHORS:20180607-155251991
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20180607-155251991
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:86903
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:08 Jun 2018 14:49
Last Modified:15 Nov 2021 20:43

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