Now showing items 21-26 of 26

    • A Study in Preference Elicitation under Uncertainty 

      Hines, Greg (University of Waterloo, 2011-08-30)
      In many areas of Artificial Intelligence (AI), we are interested in helping people make better decisions. This help can result in two advantages. First, computers can process large amounts of data and perform quick ...
    • Surface Partitioning for 3+2-axis Machining 

      Roman Flores, Armando (University of Waterloo, 2007-08-01)
      Despite the inbuilt advantages offered by 5-axis machining, the manufacturing industry has not widely adopted this technology due to the high cost of machines and insufficient support from CAD/CAM systems. Companies are ...
    • Toward Secure Trust and Reputation Systems for Electronic Marketplaces 

      Kerr, Reid Charles (University of Waterloo, 2007-05-03)
      In electronic marketplaces, buying and selling agents may be used to represent buyers and sellers respectively. When these marketplaces are large, repeated transactions between traders may be rare. This makes it difficult ...
    • Traffic Rule Checking and Validation 

      Stewart, Connor (University of Waterloo, 2024-02-15)
      This thesis presents a comprehensive exploration of traffic rule verification systems for diverse junction types, addressing key challenges in formalizing rules, determining violation thresholds, and covering a wide spectrum ...
    • Variational Inference for Text Generation: Improving the Posterior 

      Balasubramanian, Vikash (University of Waterloo, 2020-08-10)
      Learning useful representations of data is a crucial task in machine learning with wide ranging applications. In this thesis we explore improving representations of models based on variational inference by improving the ...
    • Weakly-supervised Semantic Segmentation with Regularized Loss Hyperparameter Search 

      Ji, Zongliang (University of Waterloo, 2021-09-20)
      Weakly supervised segmentation signi cantly reduces user annotation e ort. Recently, regularized loss was proposed for single object class segmentation under image-level weak supervision. Regularized loss consists of ...

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