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Filtering by: Creator Clukey, Darrell Frank Remove constraint Creator: Clukey, Darrell Frank Committee Member Wong, Weng-Keen Remove constraint Committee Member: Wong, Weng-Keen

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  • Learning to coordinate in sparse asymmetric multiagent systems

    Creator:
    Dixit, Gaurav
    Abstract:
    Multiagent learning offers a rich framework to address challenging real-world problems such as remote exploration and healthcare coordination, which require autonomous agents to express elaborate interactions. To be effective in such systems, agents must collectively reason about and pursue high-level, long-term, and possibly nebulous objectives while adapting their strategy to...
    Resource Type:
    Dissertation

  • Investigating Latent State and Uncertainty Representations in Reinforcement Learning

    Creator:
    Koul, Anurag
    Abstract:
    Learning latent space representations of high-dimensional world states has been at the core of recent rapid growth in reinforcement learning(RL). At the same time, RL algo- rithms have suffered from ignored uncertainties in the predicted estimates of model-free or model-based methods. In our work, we investigate both of these aspects...
    Resource Type:
    Dissertation

  • Local Signal Detection on Irregular Domains with Spatially Varying Coefficient Model

    Creator:
    Zhang, Chengzhu
    Abstract:
    In areas such as spatial analysis and time series analysis, it is essential to understand and quantify spatial or temporal heterogeneity. In this dissertation, we focus on a spatially varying coefficient model, in which spatial heterogeneity is accommodated by allowing the regression coefficients to vary in a given spatial domain....
    Resource Type:
    Dissertation
    Full Text:
    terms of regression coefficients are introduced. For example, the bridge regression (Frank and Friedman

  • A study of methods for fine-grained object classification of arthropod specimens

    Creator:
    Lin, Junyuan
    Abstract:
    Object categorization is one of the fundamental topics in computer vision research. Most current work in object categorization aims to discriminate among generic object classes with gross differences. However, many applications require much finer distinctions. This thesis focuses on the design, evaluation and analysis of learning algorithms for fine- grained...
    Resource Type:
    Masters Thesis