11 citations · 13 across the 6 of their papers we have counts for
16 papers
Private Graph Property Testing
Hendrik Fichtenberger, Abigail Gentle, Tamalika Mukherjee +1
Graph property testing asks whether a massive graph satisfies a given property, or is far from doing so, using only a sublinear number of queries to the graph. Since property teste…
A Differentially Private Clustering Algorithm for Well-Clustered Graphs
Weiqiang He, Hendrik Fichtenberger, Pan Peng
We study differentially private (DP) algorithms for recovering clusters in well-clustered graphs, which are graphs whose vertex set can be partitioned into a small number of sets,…
HUGE: Huge Unsupervised Graph Embeddings with TPUs
Brandon Mayer, Anton Tsitsulin, Hendrik Fichtenberger +2
Graphs are a representation of structured data that captures the relationships between sets of objects. With the ubiquity of available network data, there is increasing industrial…
Optimal Fully Dynamic -Center Clustering for Adaptive and Oblivious Adversaries
MohammadHossein Bateni, Hossein Esfandiari, Hendrik Fichtenberger +4
In fully dynamic clustering problems, a clustering of a given data set in a metric space must be maintained while it is modified through insertions and deletions of individual poin…
Approximately Counting Subgraphs in Data Streams
Hendrik Fichtenberger, Pan Peng
Estimating the number of subgraphs in data streams is a fundamental problem that has received great attention in the past decade. In this paper, we give improved streaming algorith…
Constant matters: Fine-grained Complexity of Differentially Private Continual Observation
Hendrik Fichtenberger, Monika Henzinger, Jalaj Upadhyay
We study fine-grained error bounds for differentially private algorithms for counting under continual observation. Our main insight is that the matrix mechanism when using lower-tr…