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Filtering by: Creator Slawin, Alexandra M. Remove constraint Creator: Slawin, Alexandra M. Committee Member Tadepalli, Prasad Remove constraint Committee Member: Tadepalli, Prasad Degree Level Doctoral Remove constraint Degree Level: Doctoral

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  • Inclusive Software Design and Its Methods for Beyond-WIMP User Interfaces

    Creator:
    Fallatah, Abrar
    Abstract:
    While digital inclusivity researchers and software practitioners have been trying to address exclusion biases in Windows, Icons, Menus, and Pointers (WIMP) user interfaces (UIs) for a long time, little has been done to investigate if and how inclusive software design and its methods that have been devised for WIMP UIs...
    Resource Type:
    Dissertation
    Full Text:
    , Jillian Renee Emard, Denisse A Alvarado, Brett Altena, Jeremy Urann, Janani Swaminathan, Alexandra Bacula

  • 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:
    . . . . . . . . . . . . 180 M Data Appendix - CNNs poisoned by perception/action . . . . . . . . . . . . 182 TABLE OF

  • Advances in Simultaneous Translation

    Creator:
    Zheng, Renjie
    Abstract:
    Simultaneous translation, which translates concurrently with the source language speech, is widely used in many scenarios including multilateral organizations. However, it is well known to be one of the most challenging tasks for humans due to the simultaneous perception and production in two languages. On the other hand, simultaneous translation...
    Resource Type:
    Dissertation
    Full Text:
    , ..., y ∗ m) goes through the same self-attention to generate hidden self-attended state sequence c

  • Coordination for Scalable Multiple Robot Planning Under Temporal Uncertainty

    Creator:
    Marcon dos Santos, Gilberto
    Abstract:
    This dissertation incorporates coalition formation and probabilistic planning towards a domain-independent automated planning solution scalable to multiple heterogeneous robots in complex domains. The first research direction investigates the effectiveness of Task Fusion and introduces heuristics that improve task allocation and result in better quality plans, while requiring lower computational cost...
    Resource Type:
    Dissertation

  • Computing Resource Usage as a Factor of Student Success

    Creator:
    Moissinac, Béatrice
    Abstract:
    Learning Analytics and other branches of Educational Research such as Computing Education Research (CER) implicitly assume that students, especially college students, have no barriers to access learning platforms or software packages. This assumption may be attributed to such pervasive beliefs such as "everyone has a device", or "everyone can access...
    Resource Type:
    Dissertation

  • Conceptual Representations within the Social and Material Contexts of an Engineering Workplace and Academic Environments

    Creator:
    Barner, Matthew S.
    Abstract:
    Situated cognition theory emphasizes the role that social and material contexts have on learning and knowledge application. Several studies of engineering workplace environments have noted differences between the social and material contexts of the workplace and those of undergraduate engineering education. No existing research has studied the social and material...
    Resource Type:
    Dissertation

  • 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