Global ETD Search

Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.

Results

Showing 1 to 7 of 7 for “"Bayesian Regularization"”.

  1. Modelling and prediction of tire-rim slip with finite element analysis

    … neural network with 31 neurons was trained using Bayesian regularization to predict the tire-rim slip with a correlation coefficient of 0.99431.

    uoit Repository record for Modelling and prediction of tire-rim slip with finite element analysis (opens in a new tab)

  2. Change point detection for high dimensional data and valid inference for Bayesian linear models

    … change point detection and inference for Bayesian linear models. In the first project, we propose a change point detection method testing mean shift for high dimensional observations with unknown heteroscedasticity. The proposed tests target a dense alternative and a wild bootstrap …

    uiuc Repository record for Change point detection for high dimensional data and valid inference for Bayesian linear models (opens in a new tab)

  3. EMG-Based Human-in-the-Loop Bayesian Optimization to Assist Hip-Centric Activities

    … pipeline combining Hankel decomposition, Bayesian regularization, and optimized smoothing that improves composite EMG quality metrics by 108\%; (ii) machine-learning-guided initialization from anthropometric measurements that reduces convergence time by 26.5\% and improves final …

    uic

  4. A novel non-intrusive objective method to predict voice quality of service in LTE networks.

    … quality over LTE networks. In conclusion, the Bayesian Regularization algorithm with 4 neurons in the hidden layer and sigmoid symmetric transfer function was identified as the best solution with a Mean Square Error (MSE) rate of 0.001 and regression value of 0.998 measured for the testing data …

    uwtsd Repository record for A novel non-intrusive objective method to predict voice quality of service in LTE networks. (opens in a new tab)

  5. Learning to share: Bayesian approaches to sparsity and transfer

    Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-20 without embargo terms

    uiuc Repository record for Learning to share: Bayesian approaches to sparsity and transfer (opens in a new tab)