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On Computing Total Variation Distance Between Mixtures of Product Distributions
Weiming Feng, Yucheng Fu, Minji Yang +1
We study the problem of approximating the total variation distance between two mixtures of product distributions over an -dimensional discrete domain. Given two mixtures $\mathb…
Sublinear-Time Algorithms for Diagonally Dominant Systems and Applications to the Friedkin-Johnsen Model
Weiming Feng, Zelin Li, Pan Peng
We study sublinear-time algorithms for solving linear systems , where is a diagonally dominant matrix, i.e., for all $i \in […
On approximating the -divergence between two Ising models
Weiming Feng, Yucheng Fu
The -divergence is a fundamental notion that measures the difference between two distributions. In this paper, we study the problem of approximating the -divergence between t…
Approximating the Total Variation Distance between Gaussians
Arnab Bhattacharyya, Weiming Feng, Piyush Srivastava
The total variation distance is a metric of central importance in statistics and probability theory. However, somewhat surprisingly, questions about computing it algorithmically ap…
On Deterministically Approximating Total Variation Distance
Weiming Feng, Liqiang Liu, Tianren Liu
Total variation distance (TV distance) is an important measure for the difference between two distributions. Recently, there has been progress in approximating the TV distance betw…