Randomness is a fundamental problem in theoretical computer science. This research considers two questions concerning randomness. First, it examines some extremal point matching problems, exploring the dependence of matching weight with partition cardinality in vertex-weighted bipartite graphs. Second, it considers the problem of subset selection, providing several deterministic algorithms for point selection that are as good as or better than random subset selection according to various criteria.
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Details
Title
Optimal matching and deterministic sampling
Creators
Jeff Abrahamson - DU
Contributors
Ali Shokoufandeh (Advisor) - Drexel University (1970-)
Awarding Institution
Drexel University
Degree Awarded
Doctor of Philosophy (Ph.D.)
Publisher
Drexel University; Philadelphia, Pennsylvania
Resource Type
Dissertation
Language
English
Academic Unit
College of Arts and Sciences; Drexel University; Mathematics
Other Identifier
2526; 991014632051304721
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