Web15 de mai. de 2024 · Janková et al. (2024) developed the Pearson residual-based methods for goodness-of-fit testing in high-dimensional generalized linear models. They mainly focused on sparsity settings and gave a ... http://www-stat.wharton.upenn.edu/~tcai/paper/html/Transfer-Learning-GLM.html

Learning High-dimensional Generalized Linear Autoregressive …

WebWe consider high-dimensional generalized linear models with Lipschitz loss functions, and prove a nonasymptotic oracle inequality for the empirical risk minimizer with Lasso … WebThe problem of obtaining an optimal spline with free knots is tantamount to minimizing derivatives of a nonlinear differentiable function over a Banach space on a compact … dave ashworth citroen

A Bayesian model for multivariate discrete data using spatial and ...

WebIn this work, we study the transfer learning problem under high-dimensional generalized linear models (GLMs), which aim to improve the fit on target data by borrowing information from useful source data. Given which sources to transfer, we propose a transfer learning algorithm on GLM, ... WebIn this paper, a graphic model-based doubly sparse regularized estimator is discussed under the high dimensional generalized linear models, that utilizes the graph … WebVector autoregressive models characterize a variety of time series in which linear combinations of current and past observations can be used to accurately predict ... black and glass shower screen