3 papers
cs.LG2026
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…
stat.ML2026
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…
cs.CR2025
Byzantine-Robust Federated Learning Using Generative Adversarial Networks
Usama Zafar, André M. H. Teixeira, Salman Toor
Federated learning (FL) enables collaborative model training across distributed clients without sharing raw data, but its robustness is threatened by Byzantine behaviors such as da…