I got the following email from Gerome Miklau:

Dear colleagues:

We are writing to inform you of the launch of DPCOMP.ORG.

DPCOMP.ORG is a public website designed with the following goals in mind: (1) to increase the visibility and transparency of state-of-the-art differentially private algorithms and (2) to present a principled and comprehensive empirical evaluation of these algorithms. The intended audience is both researchers who study privacy algorithms and practitioners who might deploy these algorithms.

Currently DPComp includes algorithms for answering 1- and 2-dimensional range queries. We thoroughly study algorithm accuracy and the factors that influence it and present our findings using interactive visualizations. We follow the evaluation methodology from the paper “Principled Evaluation of Differentially Private Algorithms using DPBench”. In the future we plan to extend it to cover other analysis tasks (e.g., higher dimensional data, private regression).

Our hope is that the research community will contribute to improving DPCOMP.ORG so that practitioners are exposed to emerging research developments. For example: if you have datasets which you believe would distinguish the performance of tested algorithms, new algorithms that could be included, alternative workloads, or even a new error metric, please let us know — we would like to include them.

Please share this email with interested colleagues and students. And we welcome any feedback on the website or findings.

Sincerely,

Michael Hay (Colgate University)

Ashwin Machanavajjhala (Duke University)

Gerome Miklau (UMass Amherst)