Pure Differential Privacy for Rectangle Queries via Private Partitions

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Private Heavy Hitters and Range Queries in the Shuffled Model (2019, background): “For d -dimensional range counting, the best-known upper bound on error is p log p B q ` log p n q O p d q q{ ε [27], though we note that for d “ 1 , it is possible to get a much better dependence on B [12].”
The Complexity of Differential Privacy (2017, unknown): “2 (Thresholds with pure differential privacy [41, 45]).”
Differentially Private Testing of Identity and Closeness of Discrete Distributions (2017, methodology): “[31] also uses the idea of coupling implicitly when designing differentially private partition algorithms.”