31 citations · 32 across the 2 of their papers we have counts for
5 papers · 1 filter
Classifying Partially Labeled Networked Data via Logistic Network Lasso
Nguyen Tran, Henrik Ambos, Alexander Jung
We apply the network Lasso to classify partially labeled data points which are characterized by high-dimensional feature vectors. In order to learn an accurate classifier from limi…
Localized Linear Regression in Networked Data
Alexander Jung, Nguyen Tran
The network Lasso (nLasso) has been proposed recently as an efficient learning algorithm for massive networked data sets (big data over networks). It extends the well-known least a…
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…
When is Network Lasso Accurate: The Vector Case
Nguyen Tran, Saeed Basirian, Alexander Jung
A recently proposed learning algorithm for massive network-structured data sets (big data over networks) is the network Lasso (nLasso), which extends the well- known Lasso estimato…
On the Sample Complexity of Graphical Model Selection for Non-Stationary Processes
Nguyen Q. Tran, Oleksii Abramenko, Alexander Jung
We characterize the sample size required for accurate graphical model selection from non-stationary samples. The observed data is modeled as a vector-valued zero-mean Gaussian rand…