The sample complexity of binary hypothesis testing scales as 1/JSD for the optimal LLR classifier and as 1/JSD² for a majority-vote classifier, giving JSD an operational interpretation in terms of data requirements.
Information-type measures of difference of probability distri- butions and indirect observations.Studia Scientiarum Mathematicarum Hungarica2,299–318 (1967)
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.IT 1years
2026 1verdicts
ACCEPT 1representative citing papers
citing papers explorer
-
Sample complexity bounds for the Jensen-Shannon divergence
The sample complexity of binary hypothesis testing scales as 1/JSD for the optimal LLR classifier and as 1/JSD² for a majority-vote classifier, giving JSD an operational interpretation in terms of data requirements.