WebIn this paper, we present a new method, called group sparse additive models (GroupSpAM), which can handle group sparsity in additive models. We generalize the ℓ … WebMar 4, 2024 · A Sparse Random Features algorithm, which learns a sparse non-linear predictor by minimizing an l1-regularized objective function over the Hilbert Space induced from a kernel function, which obtains a sparse solution that requires less memory and prediction time, while maintaining comparable performance on regression and …
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WebMay 22, 2024 · Sparse additive models have been successfully applied to high-dimensional data analysis due to the flexibility and interpretability of their representation. WebJul 11, 2016 · Recently, sparse unmixing (SU) of hyperspectral data has received particular attention for analyzing remote sensing images. However, most SU methods are based on the commonly admitted linear mixing model (LMM), which ignores the possible nonlinear effects (i.e., nonlinearity). In this paper, we propose a new method named robust … maps centro italia
Sparse additive machine with pinball loss - ScienceDirect
Webfor additive models. A novel sparse classification algorithm, called as group sparse additive machine (GroupSAM), is proposed under a coefficient-based regularized … WebPhone: 855-543-3784 or 301-796-3400; Fax: 301-431-6353 . Email: [email protected] maps cervati aldo