129 citations · 568 across the 49 of their papers we have counts for
5 papers · 1 filter
Robust Prediction when Features are Missing
Xiuming Liu, Dave Zachariah, Petre Stoica
Predictors are learned using past training data which may contain features that are unavailable at the time of prediction. We develop an approach that is robust against outlying mi…
Calibration tests in multi-class classification: A unifying framework
David Widmann, Fredrik Lindsten, Dave Zachariah
In safety-critical applications a probabilistic model is usually required to be calibrated, i.e., to capture the uncertainty of its predictions accurately. In multi-class classific…
Robust Risk Minimization for Statistical Learning
Muhammad Osama, Dave Zachariah, Peter Stoica
We consider a general statistical learning problem where an unknown fraction of the training data is corrupted. We develop a robust learning method that only requires specifying an…
Effect Inference from Two-Group Data with Sampling Bias
Dave Zachariah, Petre Stoica
In many applications, different populations are compared using data that are sampled in a biased manner. Under sampling biases, standard methods that estimate the difference betwee…
Inferring Heterogeneous Causal Effects in Presence of Spatial Confounding
Muhammad Osama, Dave Zachariah, Thomas B. Schön
We address the problem of inferring the causal effect of an exposure on an outcome across space, using observational data. The data is possibly subject to unmeasured confounding va…