arXiv Open Access 2022

On the Statistical Complexity of Sample Amplification

Brian Axelrod Shivam Garg Yanjun Han Vatsal Sharan Gregory Valiant

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Abstrak

The ``sample amplification'' problem formalizes the following question: Given $n$ i.i.d. samples drawn from an unknown distribution $P$, when is it possible to produce a larger set of $n+m$ samples which cannot be distinguished from $n+m$ i.i.d. samples drawn from $P$? In this work, we provide a firm statistical foundation for this problem by deriving generally applicable amplification procedures, lower bound techniques and connections to existing statistical notions. Our techniques apply to a large class of distributions including the exponential family, and establish a rigorous connection between sample amplification and distribution learning.

Topik & Kata Kunci

math.ST cs.DS cs.IT cs.LG

Penulis (5)

Brian Axelrod

Shivam Garg

Yanjun Han

Vatsal Sharan

Gregory Valiant

Format Sitasi

APA MLA BibTeX

Axelrod, B., Garg, S., Han, Y., Sharan, V., Valiant, G. (2022). On the Statistical Complexity of Sample Amplification. https://arxiv.org/abs/2201.04315

Akses Cepat

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Informasi Jurnal

Tahun Terbit: 2022
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓