9 citations · 36 across the 14 of their papers we have counts for
3 papers · 1 filter
Learning Sparse Graphs for Prediction and Filtering of Multivariate Data Processes
Arun Venkitaraman, Dave Zachariah
We address the problem of prediction of multivariate data process using an underlying graph model. We develop a method that learns a sparse partial correlation graph in a tuning-fr…
A Connectedness Constraint for Learning Sparse Graphs
Martin Sundin, Arun Venkitaraman, Magnus Jansson +1
Graphs are naturally sparse objects that are used to study many problems involving networks, for example, distributed learning and graph signal processing. In some cases, the graph…
Predicting Graph Signals using Kernel Regression where the Input Signal is Agnostic to a Graph
Arun Venkitaraman, Saikat Chatterjee, Peter Händel
We propose a kernel regression method to predict a target signal lying over a graph when an input observation is given. The input and the output could be two different physical qua…