129 citations · 568 across the 49 of their papers we have counts for
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Calibration tests beyond classification
David Widmann, Fredrik Lindsten, Dave Zachariah
Most supervised machine learning tasks are subject to irreducible prediction errors. Probabilistic predictive models address this limitation by providing probability distributions…
Diagnostic Tool for Out-of-Sample Model Evaluation
Ludvig Hult, Dave Zachariah, Petre Stoica
Assessment of model fitness is a key part of machine learning. The standard paradigm is to learn models by minimizing a chosen loss function averaged over training data, with the a…
Surprises in adversarially-trained linear regression
Antônio H. Ribeiro, Dave Zachariah, Thomas B. Schön
State-of-the-art machine learning models can be vulnerable to very small input perturbations that are adversarially constructed. Adversarial training is an effective approach to de…
Tuned Regularized Estimators for Linear Regression via Covariance Fitting
Per Mattsson, Dave Zachariah, Petre Stoica
We consider the problem of finding tuned regularized parameter estimators for linear models. We start by showing that three known optimal linear estimators belong to a wider class…