9 citations · 28 across the 11 of their papers we have counts for
3 papers · 1 filter
Communication-Efficient Triangle Counting under Local Differential Privacy
Jacob Imola, Takao Murakami, Kamalika Chaudhuri
Triangle counting in networks under LDP (Local Differential Privacy) is a fundamental task for analyzing connection patterns or calculating a clustering coefficient while strongly…
Privacy Amplification Via Bernoulli Sampling
Jacob Imola, Kamalika Chaudhuri
Balancing privacy and accuracy is a major challenge in designing differentially private machine learning algorithms. One way to improve this tradeoff for free is to leverage the no…
Online -means Clustering on Arbitrary Data Streams
Robi Bhattacharjee, Jacob Imola, Michal Moshkovitz +1
We consider online -means clustering where each new point is assigned to the nearest cluster center, after which the algorithm may update its centers. The loss incurred is the s…