Browsing by Subject "Sparsity"

Now showing items 1-4 of 4

    • Bayesian Shrinkage: Computation, Methods and Theory 
      Chakraborty, Antik (2018-08-06)
      Sparsity is a standard structural assumption that is made while modeling high-dimensional statistical parameters. This assumption essentially entails a lower dimensional embedding of the high-dimensional parameter thus ...
    • Feature Selection for Unsupervised and Supervised Learning 
      Sui, Xiaopeng (2018-11-01)
      Unsupervised and semi-supervised learning are explored in convex clustering with metric learning while supervised learning is explored in a novel feature selection method. First, we evaluate the performance of convex ...
    • Sparsity in Varying-coefficient Regression and Covariance Matrix Estimation 
      Kim, Rakheon (2022-04-20)
      This dissertation discusses how we can exploit sparsity, a statistical assumption that only a small number of relationships between variables are non-zero, in the model selection for regression and covariance matrix ...
    • Statistical Inference for Multi-view Data 
      Zhang, Yunfeng (2020-07-10)
      Multi-view data, that is matched sets of measurements on the same subjects, have become increasingly common with technological advances in genomics, neuroscience and wearable technologies, etc. Despite its prevalence, ...