activity
20132019
most citedDe-noising procedures for frame operators

1 citations · 1 across the 1 of their papers we have counts for

collaborators

5 papers

stat.ML2019

A global approach for learning sparse Ising models

Daniela De Canditiis

We consider the problem of learning the link parameters as well as the structure of a binary-valued pairwise Markov model. Under sparsity assumption, we propose a method based on $…

stat.ME2019

Learning Gaussian Graphical Models by symmetric parallel regression technique

Daniela De Canditiis, Armando Guardasole

In this contribution we deal with the problem of learning an undirected graph which encodes the conditional dependence relationship between variables of a complex system, given a s…

stat.ME2019

Simultaneous nonparametric regression in RADWT dictionaries

Daniela De Canditiis, Italia De Feis

A new technique for nonparametric regression of multichannel signals is presented. The technique is based on the use of the Rational-Dilation Wavelet Transform (RADWT), equipped wi…

stat.ME2017

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…

stat.ME20131 cited

De-noising procedures for frame operators

Daniela De Canditiis, Marianna Pensky, Patrick J. Wolfe

The present paper provides a comprehensive study of de-noising properties of frames and, in particular, tight frames, which constitute one of the most popular tools in contemporary…