All reports by Author John Peebles:

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TR20-140
| 14th September 2020
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Ilias Diakonikolas, Themis Gouleakis, Daniel Kane, John Peebles, Eric Price#### Optimal Testing of Discrete Distributions with High Probability

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TR17-133
| 7th September 2017
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Ilias Diakonikolas, Themis Gouleakis, John Peebles, Eric Price#### Sample-Optimal Identity Testing with High Probability

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TR16-178
| 11th November 2016
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Ilias Diakonikolas, Themis Gouleakis, John Peebles, Eric Price#### Collision-based Testers are Optimal for Uniformity and Closeness

Comments: 1

Ilias Diakonikolas, Themis Gouleakis, Daniel Kane, John Peebles, Eric Price

We study the problem of testing discrete distributions with a focus on the high probability regime.

Specifically, given samples from one or more discrete distributions, a property $\mathcal{P}$, and

parameters $0< \epsilon, \delta <1$, we want to distinguish {\em with probability at least $1-\delta$}

whether these distributions satisfy $\mathcal{P}$ ...
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Ilias Diakonikolas, Themis Gouleakis, John Peebles, Eric Price

We study the problem of testing identity against a given distribution (a.k.a. goodness-of-fit) with a focus on the high confidence regime. More precisely, given samples from an unknown distribution $p$ over $n$ elements, an explicitly given distribution $q$, and parameters $0< \epsilon, \delta < 1$, we wish to distinguish, {\em ... more >>>

Ilias Diakonikolas, Themis Gouleakis, John Peebles, Eric Price

We study the fundamental problems of (i) uniformity testing of a discrete distribution,

and (ii) closeness testing between two discrete distributions with bounded $\ell_2$-norm.

These problems have been extensively studied in distribution testing

and sample-optimal estimators are known for them~\cite{Paninski:08, CDVV14, VV14, DKN:15}.

In this work, we show ... more >>>