On Semi-Supervised Estimation of Distributions
Autor: | Erol, H. S. Melihcan, Sula, Erixhen, Zheng, Lizhong |
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Rok vydání: | 2023 |
Předmět: | |
Druh dokumentu: | Working Paper |
Popis: | We study the problem of estimating the joint probability mass function (pmf) over two random variables. In particular, the estimation is based on the observation of $m$ samples containing both variables and $n$ samples missing one fixed variable. We adopt the minimax framework with $l^p_p$ loss functions, and we show that the composition of uni-variate minimax estimators achieves minimax risk with the optimal first-order constant for $p \ge 2$, in the regime $m = o(n)$. Comment: Presented in ISIT-2023 |
Databáze: | arXiv |
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