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Skip to Search Results- 1Behsaz, Babak
- 1Berube, Paul N. J.
- 1Cheng, Hao
- 1Fokaefs, Marios-Eleftherios
- 1Idrissov, Agzam Y.
- 1Jullion, Zachary M
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Fall 2012
Recent proliferation of low-cost and lightweight GPS tracking devices led to a large increase in the amounts of collected mobility data. The rapidly emerging field of location-based services requires accurate and informative knowledge mining from these large quantities of data. One such mobility...
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Fall 2017
Density-based clustering methods extract high density clusters which are separated by regions of lower density. HDBSCAN* is an existing algorithm for producing a density-based cluster hierarchy. To obtain clusters from this hierarchy it includes an instance of FOSC(Framework for Optimal Selection...
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Fall 2012
In this thesis, we present some approximation algorithms for the following clustering problems: Minimum Sum of Radii (MSR), Minimum Sum of Diameters (MSD), and Unsplittable Capacitated Facility Location. Given a metric (V, d) and an integer k, we consider the problem of partitioning the points...
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Fall 2016
In this thesis, we present approximation algorithms for various NP-hard vehicle routing problems, as well as for a related maximum group coverage problem. Our main contribution is a framework to build good constant-factor approximation algorithms for variants of the multi-depot $k$-travelling...
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Fall 2015
In this thesis, we consider two closely related clustering problems, Min Sum k-Clustering (MSkC) and Balanced k-Median (BkM). In Min Sum k-clustering, one is given a graph and a parameter k, and has to partition the vertices in the graph into k clusters to minimize the sum of pairwise distances...
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Spring 2023
In this thesis, we present Approximation Schemes for the Min Sum k Clustering problem on a number of classes of graph metrics. In Min Sum k Clustering problem introduced by Sahni and Gonzalez [22] in 1976, given a graph G(V, E) with metric edge costs and parameter k, we are asked to partition V...
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Fall 2013
Due to its wide application in various fields, clustering, as a fundamental unsupervised learning problem, has been intensively investigated over the past few decades. Unfortunately, standard clustering formulations are known to be computationally intractable. Although many convex relaxations of...
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Fall 2018
Identifying the peptide sequence from a mass spectrum is done either by database search or De novo peptide sequencing. This thesis focuses on identification of peptides by using database search, which is a process where an MS/MS spectrum is searched against an entire database of spectra...
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Spring 2011
In this thesis, we present our work on two combinatorial optimization problems. The first problem is the Bandpass problem, and we designed a linear time exact algorithm for the 3-column case. The other work is on the Complementary Maximal Strip Recovery problem, for which we designed a...
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Fall 2010
Software can be considered a live entity, as it undergoes many alterations throughout its lifecycle. Therefore, code can become rather complex and difficult to understand. More specifically in object-oriented systems, classes may become very large and less cohesive. In order to identify such...