Testing Support Size More Efficiently Than Learning Histograms

v1v2v3 (latest)

Testing Support Size More Efficiently Than Learning Histograms

Symposium on the Theory of Computing (STOC), 2024

24 October 2024

Renato Ferreira Pinto Jr.

Nathaniel Harms

ArXiv (abs)PDF HTML

Papers citing "Testing Support Size More Efficiently Than Learning Histograms"

8 / 8 papers shown

Title
Estimating the Effective Support Size in Constant Query ComplexitySIAM Symposium on Simplicity in Algorithms (SOSA), 2022 Shyam Narayanan Jakub Tvetek 162 2 0 21 Nov 2022
Polynomial methods in statistical inference: theory and practiceFoundations and Trends in Communications and Information Theory (FTCIT), 2020 Yihong Wu Pengkun Yang 105 19 0 15 Apr 2021
VC Dimension and Distribution-Free Sample-Based Testing Eric Blais Renato Ferreira Pinto Nathaniel Harms 153 15 0 07 Dec 2020
Unified Sample-Optimal Property Estimation in Near-Linear TimeNeural Information Processing Systems (NeurIPS), 2019 Yi Hao A. Orlitsky 258 20 0 08 Nov 2019
The Broad Optimality of Profile Maximum LikelihoodNeural Information Processing Systems (NeurIPS), 2019 Yi Hao A. Orlitsky 206 29 0 10 Jun 2019
Local moment matching: A unified methodology for symmetric functional estimation and distribution estimation under Wasserstein distance Yanjun Han Jiantao Jiao Tsachy Weissman 205 41 0 23 Feb 2018
The Optimal Sample Complexity of PAC Learning Steve Hanneke 296 155 0 02 Jul 2015
Chebyshev polynomials, moment matching, and optimal estimation of the unseenAnnals of Statistics (Ann. Stat.), 2015 Yihong Wu Pengkun Yang 250 113 0 06 Apr 2015