In this paper, we propose a sparse tensor additive regression (STAR) that models a scalar response as a flexible nonparametric function of tensor covariates.
Mar 31, 2019 · In this paper, we propose a sparse tensor additive regression (STAR) that models a scalar response as a flexible nonparametric function of ...
Jan 1, 2021 · In this paper, we propose a sparse tensor additive regression (STAR) that models a scalar response as a exible nonparametric function of tensor ...
Summary. We present a new class of methods for high dimensional non-parametric regression and classification called sparse additive models.
Sparse additive modeling is a class of effective methods for performing high-dimensional nonparametric regression. This article develops a sparse additive ...
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We study the statistical problem of estimating a rank-one sparse tensor corrupted by additive gaussian noise, a Gaussian additive model also known as sparse ...
Abstract. We present a unified framework for estimation and analysis of generalized additive models in high dimensions. The framework defines a large class ...
Res. 2021. TLDR. A sparse tensor additive regression that models a scalar response as a flexible nonparametric function of tensor covariates and formulate the ...
Jul 22, 2020 · We study the statistical problem of estimating a rank-one sparse tensor corrupted by additive Gaussian noise, a model also known as sparse tensor PCA.
Sparse and low-rank tensor estimation via cubic sketchings. B Hao, AR Zhang, G Cheng. International conference on artificial intelligence and statistics, 1319- ...