2 papers
cs.CR2026
Private Blind Model Averaging - Distributed, Non-interactive, and Convergent
Moritz Kirschte, Sebastian Meiser, Saman Ardalan +1
Distributed differentially private learning techniques enable a large number of users to jointly learn a model without having to first centrally collect the training data. At the s…
cs.CR2024
DPM: Clustering Sensitive Data through Separation
Johannes Liebenow, Yara Schütt, Tanya Braun +3
Clustering is an important tool for data exploration where the goal is to subdivide a data set into disjoint clusters that fit well into the underlying data structure. When dealing…