241 citations · 396 across the 34 of their papers we have counts for
42 papers
The Target-Charging Technique for Privacy Accounting across Interactive Computations
Edith Cohen, Xin Lyu
We propose the \emph{Target Charging Technique} (TCT), a unified privacy analysis framework for interactive settings where a sensitive dataset is accessed multiple times using diff…
Õptimal Differentially Private Learning of Thresholds and Quasi-Concave Optimization
Edith Cohen, Xin Lyu, Jelani Nelson +2
The problem of learning threshold functions is a fundamental one in machine learning. Classical learning theory implies sample complexity of (for generalizati…
Generalized Private Selection and Testing with High Confidence
Edith Cohen, Xin Lyu, Jelani Nelson +2
Composition theorems are general and powerful tools that facilitate privacy accounting across multiple data accesses from per-access privacy bounds. However they often result in we…
On the Robustness of CountSketch to Adaptive Inputs
Edith Cohen, Xin Lyu, Jelani Nelson +3
CountSketch is a popular dimensionality reduction technique that maps vectors to a lower dimension using randomized linear measurements. The sketch supports recovering -hea…
FriendlyCore: Practical Differentially Private Aggregation
Eliad Tsfadia, Edith Cohen, Haim Kaplan +2
Differentially private algorithms for common metric aggregation tasks, such as clustering or averaging, often have limited practicality due to their complexity or to the large numb…
A Framework for Adversarial Streaming via Differential Privacy and Difference Estimators
Idan Attias, Edith Cohen, Moshe Shechner +1
Classical streaming algorithms operate under the (not always reasonable) assumption that the input stream is fixed in advance. Recently, there is a growing interest in designing ro…