3 papers
cs.CR2026
Improved Accuracy for Private Continual Cardinality Estimation in Fully Dynamic Streams via Matrix Factorization
Joel Daniel Andersson, Palak Jain, Satchit Sivakumar
We study differentially-private statistics in the fully dynamic continual observation model, where many updates can arrive at each time step and updates to a stream can involve bot…
cs.CR2025
Private Lossless Multiple Release
Joel Daniel Andersson, Lukas Retschmeier, Boel Nelson +1
Koufogiannis et al. (2016) showed a result for Laplace noise-based differentially private mechanisms: given an -DP release, a new release wi…
cs.LG2024
Streaming Private Continual Counting via Binning
Joel Daniel Andersson, Rasmus Pagh
In differential privacy, refers to problems in which we wish to continuously release a function of a dataset that is revealed one element at a time…