52 citations · 53 across the 3 of their papers we have counts for
8 papers
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…
High-dimensional classification by sparse logistic regression
Felix Abramovich, Vadim Grinshtein
We consider high-dimensional binary classification by sparse logistic regression. We propose a model/feature selection procedure based on penalized maximum likelihood with a comple…
Model selection and minimax estimation in generalized linear models
Felix Abramovich, Vadim Grinshtein
We consider model selection in generalized linear models (GLM) for high-dimensional data and propose a wide class of model selection criteria based on penalized maximum likelihood…
Model selection in regression under structural constraints
Felix Abramovich, Vadim Grinshtein
The paper considers model selection in regression under the additional structural constraints on admissible models where the number of potential predictors might be even larger tha…
Estimation of a sparse group of sparse vectors
Felix Abramovich, Vadim Grinshtein
We consider a problem of estimating a sparse group of sparse normal mean vectors. The proposed approach is based on penalized likelihood estimation with complexity penalties on the…
On Bayesian "testimation" and its application to wavelet thresholding
Felix Abramovich, Vadim Grinshtein, Athanasia Petsa +1
We consider the problem of estimating the unknown response function in the Gaussian white noise model. We first utilize the recently developed Bayesian maximum a posteriori "testim…