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Filtering by: Creator Castell, John Daniel Remove constraint Creator: Castell, John Daniel Degree Field Computer Science Remove constraint Degree Field: Computer Science Degree Level Doctoral Remove constraint Degree Level: Doctoral

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  • Understanding Software Development and Testing Practices

    Creator:
    Hilton, Michael
    Abstract:
    A bad software development process leads to wasted effort and inferior products. In order to improve a software process, it must be first understood. In this work I focus on understanding software processes. The first process we seek to understand is Continuous Integration (CI). CI systems automate the compilation, building,...
    Resource Type:
    Dissertation
    Full Text:
    Software Development and Testing Practices Abstract approved: Daniel Dig A bad software development

  • Involving older adults in the design and development of free/open source software

    Creator:
    Davidson, Jennifer L.
    Abstract:
    An age-wave is upon us where many older adults are reaching retirement. Technically experienced older adults have skills that could be directly applied to free/open source software (FOSS) communities, such as project management, programming, and/or knowledge of a rapidly growing end-user population. FOSS is a widely popular, low-cost way to...
    Resource Type:
    Dissertation

  • Machine learning methods for public policy : simulation, optimization, and visualization

    Creator:
    McGregor, Sean
    Abstract:
    Society faces many complex management problems, particularly in the area of shared public resources such as ecosystems. Existing decision making processes are often guided by personal experience and political ideology rather than state-of-the-art scientific understanding. This dissertation envisions a future in which multiple stakeholders are provided with computational tools for...
    Resource Type:
    Dissertation
    Full Text:
    , Ronald Metoyer, Prasad Tadepalli, Margaret Burnett, and John Bolte for the time and effort they

  • Resource placement, data rearrangement, and Hamiltonian cycles in torus networks

    Creator:
    Bae, Myung Mun
    Abstract:
    Many parallel machines, both commercial and experimental, have been/are being designed with toroidal interconnection networks. For a given number of nodes, the torus has a relatively larger diameter, but better cost/performance tradeoffs, such as higher channel bandwidth, and lower node degree, when compared to the hypercube. Thus, the torus is...
    Resource Type:
    Dissertation
    Full Text:
    Member (Timothy A. Budd) Committee Member (Prasad Tadepalli) uate School Representative (John P

  • Fine-Grained Object Recognition Under Limited Training Data

    Creator:
    Lam, Michael Q.
    Abstract:
    This dissertation addresses object recognition in challenging settings, where distinct object classes are visually very similar (e.g., species of birds and insects) and/or access to training examples of object classes is limited (e.g., due to the associated high costs of data annotation). In this dissertation, we present a variety of...
    Resource Type:
    Dissertation

  • Multiple Instance Multiple Label Learning with Limited Supervision

    Creator:
    Nguyen, Tam
    Abstract:
    In weak supervision learning, label information can be provided at different levels of granularity. For example, in multi-instance multi-label learning, samples are organized into bags and labels for each class are provided at the bag level. For small datasets, this approach offers means of reducing the labeling efforts. However, in...
    Resource Type:
    Dissertation
    Full Text:
    PhD committee members: Dr. Thinh Nguyen, Dr. Jinsub Kim and Dr. John Bolte providing favorable

  • Incorporating User Feedback into Machine Learning Systems

    Creator:
    Das, Shubhomoy
    Abstract:
    Although machine learning systems are often effective in real-world applications, there are situations in which they can be even better when provided with some degree of end user feedback. This is especially true when the machine learning system needs to customize itself to the end user's preferences, such as in...
    Resource Type:
    Dissertation
    Full Text:
    systems. I am grateful that Dr. John Dilles volunteered to serve as the Graduate Council Representative

  • Simulator-Defined MDP Planning with Applications in Natural Resource Management

    Creator:
    Alkaee Taleghan, Majid
    Abstract:
    This work is inspired by problems in natural resource management centered on the challenge of invasive species. Computing optimal management policies for maintaining ecosystem sustainable is challenging. Many ecosystem management problems can be formulated as MDP (Markov Decision Process) planning problems. In a simulator-defined MDP, the Markovian dynamics and rewards...
    Resource Type:
    Dissertation
    Full Text:
    Hutchinson, and John Dilles, for their constructive comments on my research. I would like to acknowledge all

  • Machine Learning Techniques to Model Species Interactions and Distributions Under Imperfect Detection

    Creator:
    Seo, Eugene
    Abstract:
    Ecological domains seeking to understand the environment and the behavior of species have received little attention in machine learning (ML), despite the fact that environmental changes have a significant impact on humans as well as ecosystems. Some ecological problems can be formulated similarly to other common ML applications, but there...
    Resource Type:
    Dissertation
    Full Text:
    John Kilbride for their insightful comments on birds and remote sensing and for their willingness to

  • Predicting and Improving Throughput, Responsiveness and Battery Life of Computer Systems by Machine Learning

    Creator:
    Li, Yunfan
    Abstract:
    The Machine Learning (ML) algorithms are increasingly explored in varies of fields including designing and optimizing computer systems. Recent research, such as optimizing memory/cache prefetching by ML training or predicting traffic pattern in throughput processors, also exhibits a promising future of introducing ML into computer system design and optimization. Throughput...
    Resource Type:
    Dissertation