A randomized (1±ε)-approximation algorithm for TV distance between k-mixtures of product distributions runs in poly((nq)^k, 1/ε) time, with exact poly(n, 2^{O(k)}) deterministic algorithm for Boolean subcubes and #P-hardness for k=Θ(n).
and Sokal, Alan D
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.DS 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
On Computing Total Variation Distance Between Mixtures of Product Distributions
A randomized (1±ε)-approximation algorithm for TV distance between k-mixtures of product distributions runs in poly((nq)^k, 1/ε) time, with exact poly(n, 2^{O(k)}) deterministic algorithm for Boolean subcubes and #P-hardness for k=Θ(n).