Sparse additive models are essentially a functional version of the grouped lasso of Yuan and Lin. They are also closely related to the COSSO model of Lin and Zhang but decouple smoothing and sparsity, enabling the use of arbitrary non-parametric smoothers.
Jul 23, 2020 · Sparse additive models have been successfully applied to high-dimensional data analysis due to the flexibility and interpretability of their ...
Abstract—Sparse additive models have been successfully applied to high-dimensional data analysis due to the flexibility.
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Sparse additive models are essentially a functional version of the grouped lasso of Yuan and Lin. They are also closely related to the COSSO model of Lin and ...
Missing: Modal | Show results with:Modal
Apr 9, 2008 · We present a new class of methods for high-dimensional non- parametric regression and classification called sparse additive models. (SpAM).
Missing: Modal | Show results with:Modal
A new robust regression method is proposed, called as sparse modal additive model (SpMAM), by integrating the modal regression metric, the data-dependent ...
Sparse additive modeling is a class of effective methods for performing high-dimensional nonparametric regression. This article develops a sparse additive model ...
Missing: Modal | Show results with:Modal
Abstract. We present a unified framework for estimation and analysis of generalized additive models in high dimensions. The framework defines a large class ...
Missing: Modal | Show results with:Modal
Apr 13, 2022 · Sparse additive modeling is a class of effective methods for performing high-dimensional nonparametric regression. This article develops a ...
Missing: Modal | Show results with:Modal
Sparse additive models have been successfully applied to high-dimensional data analysis due to the flexibility and interpretability of their representation.