Fetching the paper…
Reading the bibliography…
Given samples from an unknown distribution $p$, is it possible to distinguish whether $p$ belongs to some class of distributions $\mathcal{C}$ versus $p$ being far from every distribution in $\mathcal{C}$? This fundamental question has received tremendous attention in statistics, focusing primarily on asymptotic analysis, and more recently in information theory and theoretical computer science, where the emphasis has been on small sample size and computational complexity.
Statistical Methods for Research Workers
Ronald Aylmer Fisher · 1925
Earlier work this paper cites.
Asymptotic minimax character of the sample distribution function and of the classical multinomial estimator
A. Dvoretzky, J. Kiefer, and J. Wolfowitz · 1956
Earlier work this paper cites.
Statistical Inference under Order Restrictions
R. E. Barlow, D. J. Bartholomew, J. M. Bremner, and H. D. Brunk · 1972
Earlier work this paper cites.
The analysis of categorical data from complex sample surveys: chi-squared tests for goodness of fit and independence in two-way tables
Jon NK Rao and Alastair J Scott · 1981
Earlier work this paper cites.
Estimating a density under order restrictions: Nonasymptotic minimax risk
Lucien Birgé · 1987
Earlier work this paper cites.
The tight constant in the Dvoretzky-Kiefer-Wolfowitz inequality
Pascal Massart · 1990
Earlier work this paper cites.
Combinatorial property testing (a survey)
Oded Goldreich · 1998
Earlier work this paper cites.
Testing random variables for independence and identity
Tugkan Batu, Eldar Fischer, Lance Fortnow, Ravi Kumar, Ronitt Rubinfeld, and Patrick White · 2001
Earlier work this paper cites.
The art of uninformed decisions: A primer to property testing
Eldar Fischer · 2001
Earlier work this paper cites.
On choosing and bounding probability metrics
Alison L. Gibbs and Francis E. Su · 2002
Earlier work this paper cites.
Sublinear algorithms for testing monotone and unimodal distributions
Tuğkan Batu, Ravi Kumar, and Ronitt Rubinfeld · 2004
Earlier work this paper cites.
Testing for monotone increasing hazard rate
Peter Hall and Ingrid Van Keilegom · 2005
Earlier work this paper cites.
Testing statistical hypotheses
Erich L Lehmann and Joseph P Romano · 2006
Earlier work this paper cites.
Sublinear-time algorithms
Ronitt Rubinfeld · 2006
Earlier work this paper cites.
Testing k-wise and almost k-wise independence
Noga Alon, Alexandr Andoni, Tali Kaufman, Kevin Matulef, Ronitt Rubinfeld, and Ning Xie · 2007
Cited alongside, same era.
A coincidence-based test for uniformity given very sparsely sampled discrete data
Liam Paninski · 2008
Cited alongside, same era.
Property testing: A learning theory perspective
Dana Ron · 2008
Cited alongside, same era.
Estimation of a discrete monotone density
Hanna K. Jankowski and Jon A. Wellner · 2009
Cited alongside, same era.
Testing monotone continuous distributions on high-dimensional real cubes
Michal Adamaszek, Artur Czumaj, and Christian Sohler · 2010
Cited alongside, same era.
Estimation of a k k -monotone density: characterizations, consistency and minimax lower bounds
Fadoua Balabdaoui and Jon A. Wellner · 2010
Cited alongside, same era.
Learning mixtures of structured distributions over discrete domains
Siu On Chan, Ilias Diakonikolas, Rocco A. Servedio, and Xiaorui Sun · 2013
Later among the works it cites.
Testing properties of collections of distributions
Reut Levi, Dana Ron, and Ronitt Rubinfeld · 2013
Later among the works it cites.
Efficient compression of monotone and m m -modal distributions
Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, and Ananda Theertha Suresh · 2014
Later among the works it cites.
Efficient density estimation via piecewise polynomial approximation
Siu On Chan, Ilias Diakonikolas, Rocco A. Servedio, and Xiaorui Sun · 2014
Later among the works it cites.
Optimal algorithms for testing closeness of discrete distributions
Siu-On Chan, Ilias Diakonikolas, Gregory Valiant, and Paul Valiant · 2014
Later among the works it cites.
Log-concavity and strong log-concavity: a review
Adrien Saumard and Jon A Wellner · 2014
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Theoretical properties of the log-concave maximum likelihood estimator of a multidimensional density
Madeleine Cule and Richard Samworth · 2010
Cited alongside, same era.
Categorical data analysis
Alan Agresti and Maria Kateri · 2011
Cited alongside, same era.
Testing monotonicity of distributions over general partial orders
Arnab Bhattacharyya, Eldar Fischer, Ronitt Rubinfeld, and Paul Valiant · 2011
Cited alongside, same era.
Maximum likelihood estimation and confidence bands for a discrete log-concave distribution, 2011
Fadoua Balabdaoui, Hanna Jankowski, and Kaspar Rufibach · 2011
Cited alongside, same era.
Estimating the unseen: An n / log n n/\log n -sample estimator for entropy and support size, shown optimal via new CLTs
Gregory Valiant and Paul Valiant · 2011
Cited alongside, same era.
Competitive classification and closeness testing
Jayadev Acharya, Hirakendu Das, Ashkan Jafarpour, Alon Orlitsky, Shengjun Pan, and Ananda Theertha Suresh · 2012
Cited alongside, same era.
Later among the works it cites.
An automatic inequality prover and instance optimal identity testing
Gregory Valiant and Paul Valiant · 2014
Later among the works it cites.
Testing Poisson Binomial Distributions
Jayadev Acharya and Constantinos Daskalakis · 2015
Closest in time.
Sample-optimal density estimation in nearly-linear time
Jayadev Acharya, Ilias Diakonikolas, Jerry Li, and Ludwig Schmidt · 2015
Closest in time.
A survey on distribution testing: your data is big, but is it blue
Clément L Canonne · 2015
Closest in time.
Personal communication, February 2015
Clement Canonne, Ilias Diakonikolas, Themis Gouleakis, and Ronitt Rubinfeld · 2015
Closest in time.
Testing shape restrictions of discrete distributions
Clement Canonne, Ilias Diakonikolas, Themis Gouleakis, and Ronitt Rubinfeld · 2015
Closest in time.
On learning distributions from their samples
Sudeep Kamath, Alon Orlitsky, Dheeraj Pichapati, and Ananda T. Suresh · 2015
Closest in time.