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Filtering by: Creator Mercene-Mutia, Maria Theresa Remove constraint Creator: Mercene-Mutia, Maria Theresa Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science

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  • Interactive visualization of diversity in multivariate data sets unified across fields of study

    Creator:
    Pham, Tuan N. T.
    Abstract:
    The study of the diversity of multivariate objects shares common characteristics across disciplines, including ecology and organizational management. Nevertheless, experts in these two disciplines have adopted somewhat separate diversity concepts and analysis techniques, limiting the ability of potentially sharing and cross comparing these concerns. Moreover, while complex diversity data may...
    Resource Type:
    Dissertation
    Full Text:
    Remillard, and Theresa Valentine for offering me the resources in conducting this project. Our work on

  • Interpretable Machine Learning: Applications in Biology and Genomics

    Creator:
    Danaee, Padideh
    Abstract:
    Machine learning (ML) and deep learning (DL) models impact our daily lives with applications in natural language modeling, image analysis, healthcare, genomics, and bioinformatics. The exponential growth of biological sequence data necessitates accompanying advances in computational methods. Although deep learning is highly effective for detecting and classifying biological sequences, challenges...
    Resource Type:
    Dissertation

  • Visualization of N-ary Relationships

    Creator:
    Qu, Botong
    Abstract:
    N-ary relationships, which relate N entities where N is not necessarily two, are omnipresent in real life. In this thesis, we develop a visualization technique for N-ary relationships. First, we propose a visual metaphor that utilizes vertices and polygons to represent entities and N-ary relationships. Based on this visual metaphor,...
    Resource Type:
    Dissertation

  • Explanations and Processes to Enable Humans to Assess AI with Respect to Manipulable Properties

    Creator:
    Dodge, Jonathan E.
    Abstract:
    Assessing AI systems is difficult. Humans rely on AI systems in increasing ways, both visible and invisible, meaning a variety of stakeholders need a variety of assessment tools (e.g., a professional auditor, a developer, and an end user all have different needs). We posit that it is possible to provide...
    Resource Type:
    Dissertation
    Full Text:
    , Zhengxian Lin, Theresa Mai, Sai Raja, Caleb Matthews, Nicholas Kiddle, Evan Newman, Christopher Perdriau