Now showing items 1-5 of 5

    • Data Depth Inference for Difficult Data 

      Ramsay, Kelly (University of Waterloo, 2022-07-18)
      We explore various ways in which a robust, nonparametric statistical tool, the data depth function can be used to conduct inference on data which could be described as difficult. This can include data which are difficult ...
    • Enhanced Backward Multiple Change-Point Detection 

      Pirnia, Shahab (University of Waterloo, 2023-05-09)
      Many statistical tools are built upon a specific set of assumptions on the distribution of the data at hand. However, the distribution of the observations in the dataset may not remain constant and may change due to some ...
    • Large Data-to-Text Generation 

      Sarangian, Varnan (University of Waterloo, 2023-05-16)
      This thesis presents a domain-driven approach to sports game summarization, a specific instance of large data-to-text generation (DTG). We first address the data fidelity issue in the Rotowire dataset by supplementing ...
    • Robustness in Dimensionality Reduction 

      Liang, Jiaxi (University of Waterloo, 2016-04-14)
      Dimensionality reduction is widely used in many statistical applications, such as image analysis, microarray analysis, or text mining. This thesis focuses on three problems that relate to the robustness in dimension ...
    • Statistical Learning and Stochastic Process for Robust Predictive Control of Vehicle Suspension Systems 

      Mozaffari, Ahmad (University of Waterloo, 2017-09-12)
      Predictive controllers play an important role in today's industry because of their capability of verifying optimum control signals for nonlinear systems in a real-time fashion. Due to their mathematical properties, such ...

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