4 papers
Bounding User Contributions for User-Level Differentially Private Mean Estimation
V. Arvind Rameshwar, Anshoo Tandon
We revisit the problem of releasing the sample mean of bounded samples in a dataset, privately, under user-level -differential privacy (DP). We aim to derive the optim…
-Diversity: Linkage-Robustness via a Composition Theorem
V. Arvind Rameshwar, Anshoo Tandon
In this paper, we consider the problem of degradation of anonymity upon linkages of anonymized datasets. We work in the setting where an adversary links together anonymiz…
On Achievable Rates Over Noisy Nanopore Channels
V. Arvind Rameshwar, Nir Weinberger
In this paper, we consider a recent channel model of a nanopore sequencer proposed by McBain, Viterbo, and Saunderson (2024), termed the noisy nanopore channel (NNC). In essence, a…
On Improving the Composition Privacy Loss in Differential Privacy for Fixed Estimation Error
V. Arvind Rameshwar, Anshoo Tandon
This paper considers the private release of statistics of disjoint subsets of a dataset, in the setting of data heterogeneity, where users could contribute more than one sample, wi…