EquivTester Samples In Equivalence Testing Algorithm

:::info Authors:

(1) Diptarka Chakraborty, National University of Singapore, Singapore

(2) Sourav Chakraborty, Indian Statistical Institute, Kolkata;

(3) Gunjan Kumar, National University of Singapore, Singapore;

(4) Kuldeep S. Meel, University of Toronto, Toronto.

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Abstract and 1 Introduction

2 Notations and Preliminaries

3 Related Work

4 An Efficient One-Round Adaptive Algorithm and 4.1 High-Level Overview

4.2 Algorithm Description

4.3 Technical Analysis

5 Conclusion

6 Acknowledgements and References

A Missing Proofs

B An O(log log n)-query fully adaptive algorithm

Our algorithm, EquivTester, takes as input, two distributions P and Q, and a parameter ε > 0. It returns Accept if P = Q and Reject if their total variation distance dT V (P, Q) is greater than ε, both with at least 2/3 probability.

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:::info This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license.

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