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Showing 1 to 3 of 3 for “"bias-variance decomposition"”.

  1. Inference of high-dimensional linear models with time-varying coefficients

    … kernel smoothing technique and a Lasso bias-corrected ridge regression estimator using a bias-variance decomposition to address non-stationarity in the model. A hypothesis testing setup with familywise error control is presented alongside synthetic data and a real application to fMRI …

    uiuc Repository record for Inference of high-dimensional linear models with time-varying coefficients (opens in a new tab)

  2. Malice, inequality, instability, or ignorance? Disentangling the mechanisms of LLM unfairness

    … sources of model failure and obscures underlying biases. In this work, we propose a Hierarchical Bias-Variance Decomposition framework—termed BDSU—that decomposes total discrimination risk into four interpretable components: Bias (systematic global error), Disparity (group-level variance), …

    uiuc Repository record for Malice, inequality, instability, or ignorance? Disentangling the mechanisms of LLM unfairness (opens in a new tab)

  3. Quantitatively Motivated Model Development Framework: Downstream Analysis Effects of Normalization Strategies

    … methods are investigated by utilizing a decomposition of the empirical risk functions, measuring effects on model bias, variance, and irreducible error. Measurements of bias and variance are then applied as diagnostic procedures for model pre-processing and development within the unified …

    kennesaw Repository record for Quantitatively Motivated Model Development Framework: Downstream Analysis Effects of Normalization Strategies (opens in a new tab)