In this paper, we design sub-linear space streaming algorithms for estim...
Given a collection of m sets from a universe 𝒰, the Maximum Set
Coverage...
We study the top-k selection problem under the differential privacy mode...
Accesses to data stored remotely create a side channel that is known to ...
The *shuffle model* is a powerful tool to amplify the privacy guarantees...
Longitudinal data tracking under Local Differential Privacy (LDP) is a
c...
Structural Clustering (DynClu) is one of the most popular graph clusteri...
We present two new local differentially private algorithms for frequency...
Graph clustering objective functions with tunable resolution parameters ...
Resolution parameters in graph clustering represent a size and quality
t...
Finding clusters of well-connected nodes in a graph is an extensively st...
Clustering is a fundamental tool for analyzing large data sets. A rich b...
We present new results for LambdaCC and MotifCC, two recently introduced...
We outline a new approach for solving optimization problems which enforc...
We present and analyze a new framework for graph clustering based on a
s...