38 citations · 195 across the 35 of their papers we have counts for
5 papers · 1 filter
Analysis of Network Lasso for Semi-Supervised Regression
A. Jung, N. Vesselinova
We apply network Lasso to semi-supervised regression problems involving network structured data. This approach lends quite naturally to highly scalable learning algorithms in the f…
On The Complexity of Sparse Label Propagation
Alexander Jung
This paper investigates the computational complexity of sparse label propagation which has been proposed recently for processing network structured data. Sparse label propagation a…
Graph Signal Sampling via Reinforcement Learning
Oleksii Abramenko, Alexander Jung
We formulate the problem of sampling and recovering clustered graph signal as a multi-armed bandit (MAB) problem. This formulation lends naturally to learning sampling strategies u…
Machine Learning: The Basics
Alexander Jung
Machine learning (ML) has become a commodity in our every-day lives. We routinely ask ML empowered smartphones to suggest lovely food places or to guide us through a strange place.…
The Logistic Network Lasso
Henrik Ambos, Nguyen Tran, Alexander Jung
We apply the network Lasso to solve binary classification and clustering problems for network-structured data. To this end, we generalize ordinary logistic regression to non-Euclid…