mlsanityData to 7 Oct 2026

A simple polynomial-time approximation algorithm for the total variation distance between two product distributions

arXiv 2208.00740 ↗First posted 1 Aug 2022cs.DS stat.MEcited by 8

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Abstract (arXiv)

We give a simple polynomial-time approximation algorithm for the total variation distance between two product distributions.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Aug 2022.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 1; 2025: 5; 2026: 1.

8 papers.

  1. 2023Total Variation Distance Meets Probabilistic Inferencecited by 5
  2. 2024Sharp bounds on aggregate expert errorcited by 2
  3. 2025Bias Detection via Maximum Subgroup Discrepancycited by 2
  4. 2025Approximating the total variation distance between spin systemscited by 2
  5. 2025Approximating the Total Variation Distance between Gaussianscited by 1
  6. 2025On approximating the f-divergence between two Ising modelscited by 0
  7. 2025New Algorithmic Directions in Optimal Transport and Applications for Product Spacescited by 0
  8. 2026On Computing Total Variation Distance Between Mixtures of Product Distributionscited by 0