A new data structure samples any entry of the noise vector in constant time while exactly reproducing the binary tree Gaussian mechanism distribution, applied to DP CountSketches for improved range counting and join size estimation.
Title resolution pending
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
Introduces a scalable algebraic framework relating rank deficiency of generalized Vandermonde matrices for sparse steering vectors to thinned Toeplitz matrices and augmented full-ULA matrices to characterize and avoid multi-source ambiguities in thinned uniform linear arrays.
No method can guarantee simple explanations, compressed observations, and efficient exact inference simultaneously because of inherent trade-offs from sparse representation uncertainty, sample complexity, and computational hardness.
citing papers explorer
-
A Fast Gaussian Mechanism under Continual Observation, with Applications
A new data structure samples any entry of the noise vector in constant time while exactly reproducing the binary tree Gaussian mechanism distribution, applied to DP CountSketches for improved range counting and join size estimation.
-
Ambiguity Analysis and Design of Sparse Arrays via Generalized Vandermonde Rank Conditions
Introduces a scalable algebraic framework relating rank deficiency of generalized Vandermonde matrices for sparse steering vectors to thinned Toeplitz matrices and augmented full-ULA matrices to characterize and avoid multi-source ambiguities in thinned uniform linear arrays.
-
The Existential Theory of Research: Why Discovery Is Hard
No method can guarantee simple explanations, compressed observations, and efficient exact inference simultaneously because of inherent trade-offs from sparse representation uncertainty, sample complexity, and computational hardness.