Graph Learning Based on Total Variation Minimization

By Peter Berger, Manfred Buchacher, Gabor Hannak, Gerald Matz. 2018

10 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistical and Nonlinear Physics

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Aurélien Bellet
2. Valentina Zantedeschi
3. Marc Tommasi

In Statistical and Nonlinear Physics

1. Marc Tommasi
2. Aurélien Bellet
3. Valentina Zantedeschi

Citations in the corpus

• Fully Decentralized Joint Learning of Personalized Models and Collaboration Graphs (2019, background): “…and degrees in a flexible way (which encompasses some recent work from the graph signal processing community (Dong et al., 2016; Kalofolias, 2016; Berger et al., 2018)), while the separable structure is key to the de-sign of an efficient decentralized algorithm that relies only on local…”