Sep 11, 2024 · Building on Locality Sensitive Filters, we derive a simple data structure for the Approximate Near Neighbor Counting problem under differential privacy.
Building on Locality Sensitive Filters, we derive a simple data structure for the Approximate Near Neighbor Counting problem under differential privacy.
[PDF] A Simple Linear Space Data Structure for ANN with ...
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A simple data structure is derived for the Approximate Near Neighbor Counting problem under differential privacy using Locality Sensitive Filters and a ...
Sep 14, 2024 · Building on Locality Sensitive Filters, we derive a simple data structure for the Approximate Near Neighbor Counting problem under differential ...
Locality Sensitive Filters are known for offering a quasi-linear space data structure with rigorous guarantees for the Approximate Near Neighbor search ...
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Locality Sensitive Filters are known for offering a quasi-linear space data structure with rigorous guarantees for the Approximate Near Neighbor search problem.
Vector Search on Billion-Scale Data Collections · A Simple Linear Space Data Structure for ANN with Application in Differential Privacy · Pacmann : Efficient ...
The approximate range counting data structure can be used to solve the approximate nearest neighbor (ANN) problem and k-NN classification, leading to the ...
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Aug 1, 2024 · In this article, we present two differentially private algorithms for linear regression with linked data. In particular, we propose a noisy gradient method.
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