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Statistical Queries and Statistical Algorithms: Foundations and Applications

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arxiv 2004.00557 v2 pith:QDAOJF27 submitted 2020-04-01 cs.LG cs.CCstat.ML

classification cs.LGcs.CCstat.ML
keywords statisticalqueriesapplicationsgiveareasfoundationsotheralgorithms
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We give a survey of the foundations of statistical queries and their many applications to other areas. We introduce the model, give the main definitions, and we explore the fundamental theory statistical queries and how how it connects to various notions of learnability. We also give a detailed summary of some of the applications of statistical queries to other areas, including to optimization, to evolvability, and to differential privacy.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Multiple Planted Structures Below $\sqrt{n}$: An SoS Integrality Gap and an SQ Lower Bound

    cs.CC 2026-04 unverdicted novelty 7.0 of 10

    Sum-of-Squares and statistical query algorithms cannot efficiently refute or detect multiple disjoint planted cliques or bicliques below the sqrt(n) total-size threshold.

  2. LLM Priors for ERM over Programs

    cs.LG 2025-10 conditional novelty 5.0 of 10

    LLM-ERM uses LLM-proposed candidate programs plus validation-based selection to learn short program rules (parity, primality, palindromes) from about 200 examples, while SGD-trained transformers overfit.

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