1 citations · 1 across the 3 of their papers we have counts for
3 papers
SoK: Memorisation in machine learning
Dmitrii Usynin, Moritz Knolle, Georgios Kaissis
Quantifying the impact of individual data samples on machine learning models is an open research problem. This is particularly relevant when complex and high-dimensional relationsh…
(Predictable) Performance Bias in Unsupervised Anomaly Detection
Felix Meissen, Svenja Breuer, Moritz Knolle +5
Background: With the ever-increasing amount of medical imaging data, the demand for algorithms to assist clinicians has amplified. Unsupervised anomaly detection (UAD) models promi…
Bias-Aware Minimisation: Understanding and Mitigating Estimator Bias in Private SGD
Moritz Knolle, Robert Dorfman, Alexander Ziller +2
Differentially private SGD (DP-SGD) holds the promise of enabling the safe and responsible application of machine learning to sensitive datasets. However, DP-SGD only provides a bi…