activity
20222026
most citedCorrelated Noise Mechanisms for Differentially Private Learning

2 citations · 3 across the 6 of their papers we have counts for

collaborators

12 papers

cs.DS2026

Dynamic Hierarchical -Tree Decomposition and Its Applications

Gramoz Goranci, Monika Henzinger, Peter Kiss +2

We develop a new algorithmic framework for designing approximation algorithms for cut-based optimization problems on capacitated undirected graphs that undergo edge insertions and…

cs.DS2025

An Improved Quality Hierarchical Congestion Approximator in Near-Linear Time

Monika Henzinger, Robin Münk, Harald Räcke

A single-commodity congestion approximator for a graph is a compact data structure that approximately predicts the edge congestion required to route any set of single-commodity flo…

cs.DS2025

Improved Lower Bounds for Privacy under Continual Release

Bardiya Aryanfard, Monika Henzinger, David Saulpic +1

We study the problem of continually releasing statistics of an evolving dataset under differential privacy. In the event-level setting, we show the first polynomial lower bounds on…

cs.DS2025

Deterministic and Exact Fully-dynamic Minimum Cut of Superpolylogarithmic Size in Subpolynomial Time

Antoine El-Hayek, Monika Henzinger, Jason Li

We present an exact fully-dynamic minimum cut algorithm that runs in deterministic update time when the minimum cut size is at most for any ,…

cs.DS2025

Normalized Square Root: Sharper Matrix Factorization Bounds for Differentially Private Continual Counting

Monika Henzinger, Nikita P. Kalinin, Jalaj Upadhyay

The factorization norms of the lower-triangular all-ones matrix, and , play a central role in differential privacy as they are used…

cs.DS2025

Near-Optimal Differentially Private Graph Algorithms via the Multidimensional AboveThreshold Mechanism

Laxman Dhulipala, Monika Henzinger, George Z. Li +3

Many differentially private and classical non-private graph algorithms rely crucially on determining whether some property of each vertex meets a threshold. For example, for the $k…