129 citations · 568 across the 49 of their papers we have counts for
7 papers · 1 filter
How consistent is my model with the data? Information-Theoretic Model Check
Andreas Svensson, Dave Zachariah, Thomas B. Schön
The choice of model class is fundamental in statistical learning and system identification, no matter whether the class is derived from physical principles or is a generic black-bo…
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…
Regularized parametric system identification: a decision-theoretic formulation
Johan Wågberg, Dave Zachariah, Thomas B. Schön
Parametric prediction error methods constitute a classical approach to the identification of linear dynamic systems with excellent large-sample properties. A more recent regularize…
Model-Robust Counterfactual Prediction Method
Dave Zachariah, Petre Stoica
We develop a novel method for counterfactual analysis based on observational data using prediction intervals for units under different exposures. Unlike methods that target heterog…
Leontief Meets Shannon - Measuring the Complexity of the Economic System
Dave Zachariah, Paul Cockshott
We develop a complexity measure for large-scale economic systems based on Shannon's concept of entropy. By adopting Leontief's perspective of the production process as a circular f…
Online Learning for Distribution-Free Prediction
Dave Zachariah, Petre Stoica, Thomas B. Schön
We develop an online learning method for prediction, which is important in problems with large and/or streaming data sets. We formulate the learning approach using a covariance-fit…