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Graphs

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Full-Text Articles in Mathematics

Machine Learning Techniques As Applied To Discrete And Combinatorial Structures, Samuel David Schwartz Aug 2019

Machine Learning Techniques As Applied To Discrete And Combinatorial Structures, Samuel David Schwartz

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Machine Learning Techniques have been used on a wide array of input types: images, sound waves, text, and so forth. In articulating these input types to the almighty machine, there have been all sorts of amazing problems that have been solved for many practical purposes.

Nevertheless, there are some input types which don’t lend themselves nicely to the standard set of machine learning tools we have. Moreover, there are some provably difficult problems which are abysmally hard to solve within a reasonable time frame.

This thesis addresses several of these difficult problems. It frames these problems such that we can …


Hamiltonicity, Pancyclicity, And Cycle Extendability In Graphs, Deborah C. Arangno May 2014

Hamiltonicity, Pancyclicity, And Cycle Extendability In Graphs, Deborah C. Arangno

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

A significant portion of Graph Theory is devoted to determining the characteristics which guarantee the existence of long cycles.

Long cycles have roles in applications to civil engineering, chemistry, and communications, among many others, but the problem, in and of itself, of determining whether a graph has a cycle of some fixed and typically large length is one of the most important problems of both pure Mathematics and Computer Science.

A cycle containing all the vertices of the graph is called a Hamiltonian cycle, and a graph which possesses such a cycle is said to be Hamiltonian. If …