activity
20162023
most citedPrivate Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication Overhead

19 citations · 69 across the 25 of their papers we have counts for

collaborators

50 papers

cs.CR2023

Summary Reports Optimization in the Privacy Sandbox Attribution Reporting API

Hidayet Aksu, Badih Ghazi, Pritish Kamath +4

The Privacy Sandbox Attribution Reporting API has been recently deployed by Google Chrome to support the basic advertising functionality of attribution reporting (aka conversion me…

cs.DS2022

Differentially Private Heatmaps

Badih Ghazi, Junfeng He, Kai Kohlhoff +4

We consider the task of producing heatmaps from users' aggregated data while protecting their privacy. We give a differentially private (DP) algorithm for this task and demonstrate…

cs.DS2022

Private Counting of Distinct and k-Occurring Items in Time Windows

Badih Ghazi, Ravi Kumar, Pasin Manurangsi +1

In this work, we study the task of estimating the numbers of distinct and -occurring items in a time window under the constraint of differential privacy (DP). We consider severa…

cs.CC2022

Improved Inapproximability of VC Dimension and Littlestone's Dimension via (Unbalanced) Biclique

Pasin Manurangsi

We study the complexity of computing (and approximating) VC Dimension and Littlestone's Dimension when we are given the concept class explicitly. We give a simple reduction from Ma…

cs.DS2022

Anonymized Histograms in Intermediate Privacy Models

Badih Ghazi, Pritish Kamath, Ravi Kumar +1

We study the problem of privately computing the anonymized histogram (a.k.a. unattributed histogram), which is defined as the histogram without item labels. Previous works have pro…

cs.LG2022

Private Isotonic Regression

Badih Ghazi, Pritish Kamath, Ravi Kumar +1

In this paper, we consider the problem of differentially private (DP) algorithms for isotonic regression. For the most general problem of isotonic regression over a partially order…