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On Robustness to Adaptive Inputs: A Case Study of CountSketch. The performance of randomized algorithms can be considered ... ... follows so we have the context it ms the mod ms it to a Optimal Differentially Private Learning of Thresholds and Quasi-Concave Optimization. Google Tech Talks March 27, 2007 ABSTRACT Consider a giant data matrix A of N rows and D columns. At Web scale, both N ...
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Monotone Estimation Framework and its Applications for Scalable Analytics of Large Data Sets
Edith Cohen - Hot PATE: Private Aggregation of Distributions for Diverse Tasks
Generalized Private Selection and Testing with High Confidence
STOC 2023 - Session 2B - Optimal Differentially Private Learning of Thresholds and Quasi-Concave...
Sampling Techniques for Massive Data
GTAC 2015: Statistical Data Sampling
A Framework for Adversarial Streaming via Differential Privacy and Difference Estimators
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Last Updated: June 11, 2026
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