Now showing items 1-5 of 5

    • Algorithmic Behaviours of Adagrad in Underdetermined Linear Regression 

      Rambidis, Andrew (University of Waterloo, 2023-08-24)
      With the high use of over-parameterized data in deep learning, the choice of optimizer in training plays a big role in a model’s ability to generalize well due to the existence of solution selection bias. We consider the ...
    • Data Reduction Algorithms in Machine Learning and Data Science 

      Ghojogh, Benyamin (University of Waterloo, 2021-02-19)
      Raw data are usually required to be pre-processed for better representation or discrimination of classes. This pre-processing can be done by data reduction, i.e., either reduction in dimensionality or numerosity (cardinality). ...
    • Data Science for Software Maintenance 

      Inozemtseva, Laura Michelle McLean (University of Waterloo, 2017-04-26)
      Maintaining and evolving modern software systems is a difficult task: their scope and complexity mean that seemingly inconsequential changes can have far-reaching consequences. Most software development companies attempt ...
    • Micromeda: a genome property prediction pipeline and web visualization tool 

      Bergstrand, Lee (University of Waterloo, 2020-05-07)
      Understanding the distribution of biochemical pathways across microorganisms is critical to understanding these organism's evolution, ecology, and industrial applicability. Advances in genome sequencing and pathway databases ...
    • Scaling Machine Learning Data Repair Systems for Sparse Datasets 

      Attia, Omar (University of Waterloo, 2021-01-21)
      Machine learning data repair systems (e.g. HoloClean) have achieved state-of-the-art performance for the data repair problem on many datasets. However, these systems face significant challenges with sparse datasets. In ...

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