38 citations · 195 across the 35 of their papers we have counts for
8 papers · 1 filter
Basic Principles of Clustering Methods
Alexander Jung, Ivan Baranov
Clustering methods group a set of data points into a few coherent groups or clusters of similar data points. As an example, consider clustering pixels in an image (or video) if the…
Clustering in Partially Labeled Stochastic Block Models via Total Variation Minimization
Alexander Jung
A main task in data analysis is to organize data points into coherent groups or clusters. The stochastic block model is a probabilistic model for the cluster structure. This model…
Components of Machine Learning: Binding Bits and FLOPS
Alexander Jung
Many machine learning problems and methods are combinations of three components: data, hypothesis space and loss function. Different machine learning methods are obtained as combin…
On the Duality between Network Flows and Network Lasso
Alexander Jung
Many applications generate data with an intrinsic network structure such as time series data, image data or social network data. The network Lasso (nLasso) has been proposed recent…
Learning Networked Exponential Families with Network Lasso
Alexander Jung
We propose networked exponential families to jointly leverage the information in the topology as well as the attributes (features) of networked data points. Networked exponential f…
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…