… As we explain later, SPAMs can also be thought of as a … model the relationship by using
an additive model. This leads to the following optimization problem for functional sparse …

… We present a new class of models for high-dimensional nonparametric regression and …
sparse additive models (SpAM) that extend the advantages of sparse linear models to the additive…

… the problem of sparse variable selection in nonparametric additive models, with … , sparse
additive models). In this paper, we present a new method, called group sparse additive models (…

… We present a unified framework for estimation and analysis of generalized additive models
in high dimensions. The framework defines a large class of penalized regression estimators, …

… the sparse partially linear additive model (SPLAM), which combines model fitting and both
of these model … SPLAM provides a bridge between the lasso and sparse additive models. …

… From Table 1, we know that SSAM bridges sparse kernel regression and sparse additive
models. In theory, SSAM not only can exploit the interactions among features for prediction, but …

… Section 2 presents the SpAM model for classification and defines sparse group Lasso and
Slope classifiers. In Section 3 we establish the minimaxity of the proposed SpAM classifiers …

… In this paper, we use the non-parametric sparse additive model (SpAM) framework to
address this challenge. Using a combination of β and φ-mixing properties of Markov chains and …

… We consider (nonparametric) sparse additive models (SpAM) for classification. The design
of a SpAM classifier is based … Thus, consider a sparse additive model (SpAM) assuming that …

… → R is referred to as a Sparse Additive Model (SPAM), if it is of the … In this work, we consider
a generalized SPAM, allowing for … to the class of sparse additive models (SPAMs), wherein: …