141 citations · 416 across the 15 of their papers we have counts for
4 papers · 1 filter
Robust NAS under adversarial training: benchmark, theory, and beyond
Yongtao Wu, Fanghui Liu, Carl-Johann Simon-Gabriel +2
Recent developments in neural architecture search (NAS) emphasize the significance of considering robust architectures against malicious data. However, there is a notable absence o…
Assaying Out-Of-Distribution Generalization in Transfer Learning
Florian Wenzel, Andrea Dittadi, Peter Vincent Gehler +9
Since out-of-distribution generalization is a generally ill-posed problem, various proxy targets (e.g., calibration, adversarial robustness, algorithmic corruptions, invariance acr…
PopSkipJump: Decision-Based Attack for Probabilistic Classifiers
Carl-Johann Simon-Gabriel, Noman Ahmed Sheikh, Andreas Krause
Most current classifiers are vulnerable to adversarial examples, small input perturbations that change the classification output. Many existing attack algorithms cover various sett…
Metrizing Weak Convergence with Maximum Mean Discrepancies
Carl-Johann Simon-Gabriel, Alessandro Barp, Bernhard Schölkopf +1
This paper characterizes the maximum mean discrepancies (MMD) that metrize the weak convergence of probability measures for a wide class of kernels. More precisely, we prove that,…