17,481 research outputs found
Combinatorial persistency criteria for multicut and max-cut
In combinatorial optimization, partial variable assignments are called
persistent if they agree with some optimal solution. We propose persistency
criteria for the multicut and max-cut problem as well as fast combinatorial
routines to verify them. The criteria that we derive are based on mappings that
improve feasible multicuts, respectively cuts. Our elementary criteria can be
checked enumeratively. The more advanced ones rely on fast algorithms for upper
and lower bounds for the respective cut problems and max-flow techniques for
auxiliary min-cut problems. Our methods can be used as a preprocessing
technique for reducing problem sizes or for computing partial optimality
guarantees for solutions output by heuristic solvers. We show the efficacy of
our methods on instances of both problems from computer vision, biomedical
image analysis and statistical physics
Superiorization and Perturbation Resilience of Algorithms: A Continuously Updated Bibliography
This document presents a, (mostly) chronologically ordered, bibliography of
scientific publications on the superiorization methodology and perturbation
resilience of algorithms which is compiled and continuously updated by us at:
http://math.haifa.ac.il/yair/bib-superiorization-censor.html. Since the
beginings of this topic we try to trace the work that has been published about
it since its inception. To the best of our knowledge this bibliography
represents all available publications on this topic to date, and while the URL
is continuously updated we will revise this document and bring it up to date on
arXiv approximately once a year. Abstracts of the cited works, and some links
and downloadable files of preprints or reprints are available on the above
mentioned Internet page. If you know of a related scientific work in any form
that should be included here kindly write to me on: [email protected] with
full bibliographic details, a DOI if available, and a PDF copy of the work if
possible. The Internet page was initiated on March 7, 2015, and has been last
updated on March 12, 2020.Comment: Original report: June 13, 2015 contained 41 items. First revision:
March 9, 2017 contained 64 items. Second revision: March 8, 2018 contained 76
items. Third revision: March 11, 2019 contains 90 items. Fourth revision:
March 16, 2020 contains 112 item
X-ray sensor development for magnetospheric research
The ARPA-301 data on the P78-1 satellite provide information on the long-term X-ray environment; specifically, the distributions in total X-ray intensities and energy spectral parameters and the spatial extents of the X-ray sources. The average X-ray intensity near noontime was found to decrease with increasing local time whereas the opposite trend occurs around midnight. At both of these local times, the average flux increases with increasing level of geomagnetic activity. The distributions in flux are also considered for given local time intervals and these span a large dynamic range. The temporal correlation between the X-ray flux in different local time sectors is found to decrease with increasing difference in local time. The average spectral shapes do not depend significantly upon local time or geomagnetic activity
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