52 citations · 62 across the 9 of their papers we have counts for
17 papers
High-dimensional regression with a count response
Or Zilberman, Felix Abramovich
We consider high-dimensional regression with a count response modeled by Poisson or negative binomial generalized linear model (GLM). We propose a penalized maximum likelihood esti…
Statistical learning by sparse deep neural networks
Felix Abramovich
We consider a deep neural network estimator based on empirical risk minimization with l_1-regularization. We derive a general bound for its excess risk in regression and classifica…
Classification by sparse generalized additive models
Felix Abramovich
We consider (nonparametric) sparse (generalized) additive models (SpAM) for classification. The design of a SpAM classifier is based on minimizing the logistic loss with a sparse g…
Generalization Error Bounds for Multiclass Sparse Linear Classifiers
Tomer Levy, Felix Abramovich
We consider high-dimensional multiclass classification by sparse multinomial logistic regression. Unlike binary classification, in the multiclass setup one can think about an entir…
Multiclass classification by sparse multinomial logistic regression
Felix Abramovich, Vadim Grinshtein, Tomer Levy
In this paper we consider high-dimensional multiclass classification by sparse multinomial logistic regression. We propose first a feature selection procedure based on penalized ma…
Solution of linear ill-posed problems by model selection and aggregation
Felix Abramovich, Daniela De Canditiis, Marianna Pensky
We consider a general statistical linear inverse problem, where the solution is represented via a known (possibly overcomplete) dictionary that allows its sparse representation. We…