# Fair Near Neighbor Search: Independent Range Sampling in High Dimensions

@article{Aumller2020FairNN, title={Fair Near Neighbor Search: Independent Range Sampling in High Dimensions}, author={Martin Aum{\"u}ller and R. Pagh and Francesco Silvestri}, journal={Proceedings of the 39th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems}, year={2020} }

Similarity search is a fundamental algorithmic primitive, widely used in many computer science disciplines. There are several variants of the similarity search problem, and one of the most relevant is the r-near neighbor (r-NN) problem: given a radius r>0 and a set of points S, construct a data structure that, for any given query point q, returns a point p within distance at most r from q. In this paper, we study the r-NN problem in the light of fairness. We consider fairness in the sense of…

## 9 Citations

Sampling a Near Neighbor in High Dimensions — Who is the Fairest of Them All?

- Computer ScienceACM Transactions on Database Systems
- 2022

This work shows that LSH based algorithms can be made fair, without a significant loss in efficiency, and develops a data structure for fair similarity search under inner product that requires nearly-linear space and exploits locality sensitive filters.

Fair near neighbor search via sampling

- Computer ScienceSIGMOD Rec.
- 2021

This paper studies the r-NN problem in the light of individual fairness and providing equal opportunities: all points that are within distance r from the query should have the same probability to be returned.

Sub-Linear Privacy-Preserving Near-Neighbor Search

- Computer ScienceIACR Cryptol. ePrint Arch.
- 2019

This paper provides the first such algorithm, called Secure Locality Sensitive Indexing (SLSI) which has a sub-linear query time and the ability to handle honest-but-curious parties and provides information theoretic bound for the privacy guarantees.

Approximation Algorithms for Socially Fair Clustering

- Computer ScienceCOLT
- 2021

This work introduces a strengthened LP relaxation and shows that it has an integrality gap of Θ( log l log log l ) for a fixed p, and presents a bicriteria approximation algorithm, which generalizes the bicritical approximation of Abbasi et al. (2021).

Algorithmic Techniques for Independent Query Sampling

- Computer Science
- 2022

Several generic techniques are distills the existing solutions into several generic techniques that, when put together, can be utilized to solve a great variety of IQS problems with attractive performance guarantees.

Near Neighbor: Who is the Fairest of Them All?

- Computer ScienceNeurIPS
- 2019

This work shows that LSH based algorithms can be made fair, without a significant loss in efficiency, and shows an algorithm that reports a point in the r-neighborhood of a query $q$ with almost uniform probability.

Querying in the Age of Graph Databases and Knowledge Graphs

- Computer ScienceSIGMOD Conference
- 2021

This tutorial will provide a conceptual map of the data management tasks underlying these developments, paying particular attention to data models and query languages for graphs.

Improved Approximation Algorithms for Individually Fair Clustering

- Computer Science, MathematicsAISTATS
- 2022

This work extends the framework of (Charikar et al., 2002; Swamy, 2016) and devise a 16-approximation algorithm for the facility location with lp-norm cost under matroid constraint which might be of an independent interest and proposes a reduction from an individually fair clustering to a group fairness requirement proposed by Kleindessner et al. (2019).

Optimizing Fair Approximate Nearest Neighbor Searches Using Threaded B+-Trees

- Computer ScienceSISAP
- 2021

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