542 citations · 1.6k across the 85 of their papers we have counts for
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Near-Optimal Algorithms for Differentially-Private Principal Components
Kamalika Chaudhuri, Anand D. Sarwate, Kaushik Sinha
Principal components analysis (PCA) is a standard tool for identifying good low-dimensional approximations to data in high dimension. Many data sets of interest contain private or…
Convergence Rates for Differentially Private Statistical Estimation
Kamalika Chaudhuri, Daniel Hsu
Differential privacy is a cryptographically-motivated definition of privacy which has gained significant attention over the past few years. Differentially private solutions enforce…
An Online Learning-based Framework for Tracking
Kamalika Chaudhuri, Yoav Freund, Daniel Hsu
We study the tracking problem, namely, estimating the hidden state of an object over time, from unreliable and noisy measurements. The standard framework for the tracking problem i…