1 citations · 1 across the 8 of their papers we have counts for
8 papers
Adversarial Training of Linear Models under Stealthy Attacks
Lovisa Eriksson, Dave Zachariah, André M. H. Teixeira
Predictive models are widely used in many fields, but are vulnerable to false data injection attacks. To address this, detection schemes and adversarial training have been proposed…
A Robust Optimization Approach to Sparse Principal Component Analysis
David Vävinggren, Francis Bach, André M. H. Teixeira +2
While principal component analysis (PCA) is a fundamental tool for dimensionality reduction, its dense representations make it ill-suited for high-dimensional data. Existing method…
Learning plug-in surrogate endpoints for randomized experiments
Alessandro-Umberto Margueritte, Ahmet Zahid Balcıoğlu, Jesse Krijthe +2
Surrogate endpoints are used in place of long-term outcomes in randomized experiments when observing the real outcome for a large enough cohort is prohibitively expensive or imprac…
Anytime-Valid Conformal Risk Control
Bror Hultberg, Dave Zachariah, Antônio H. Ribeiro
Prediction sets provide a means of quantifying the uncertainty in predictive tasks. Using held out calibration data, conformal prediction and risk control can produce prediction se…
Kernel Learning with Adversarial Features: Numerical Efficiency and Adaptive Regularization
Antônio H. Ribeiro, David Vävinggren, Dave Zachariah +2
Adversarial training has emerged as a key technique to enhance model robustness against adversarial input perturbations. Many of the existing methods rely on computationally expens…
Learning Treatment Allocations with Risk Control Under Partial Identifiability
Sofia Ek, Dave Zachariah
Learning beneficial treatment allocations for a patient population is an important problem in precision medicine. Many treatments come with adverse side effects that are not commen…
Regularization properties of adversarially-trained linear regression
Antônio H. Ribeiro, Dave Zachariah, Francis Bach +1
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…
Externally Valid Policy Evaluation Combining Trial and Observational Data
Sofia Ek, Dave Zachariah
Randomized trials are widely considered as the gold standard for evaluating the effects of decision policies. Trial data is, however, drawn from a population which may differ from…