ML Anthology

Efficient Distance Approximation for Structured High-Dimensional Distributions via Learning

Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S Meel, N. V. Vinodchandran
NeurIPS 2020
/neurips/2020/bhattacharyya2020neurips-efficient/

Abstract

We design efficient distance approximation algorithms for several classes of well-studied structured high-dimensional distributions. Specifically, we present algorithms for the following problems (where dTV is the total variation distance):

PDF NeurIPS Semantic Scholar

Cite

Text

Bhattacharyya et al. "Efficient Distance Approximation for Structured High-Dimensional Distributions via Learning." Neural Information Processing Systems, 2020.

Markdown

[Bhattacharyya et al. "Efficient Distance Approximation for Structured High-Dimensional Distributions via Learning." Neural Information Processing Systems, 2020.](https://mlanthology.org/neurips/2020/bhattacharyya2020neurips-efficient/)

BibTeX

@inproceedings{bhattacharyya2020neurips-efficient,
  title     = {{Efficient Distance Approximation for Structured High-Dimensional Distributions via Learning}},
  author    = {Bhattacharyya, Arnab and Gayen, Sutanu and Meel, Kuldeep S and Vinodchandran, N. V.},
  booktitle = {Neural Information Processing Systems},
  year      = {2020},
  url       = {https://mlanthology.org/neurips/2020/bhattacharyya2020neurips-efficient/}
}