Difference between revisions of "Open Problems:87"
(Created page with "{{Header |source=focs17 |who=Gautam Kamath |title=Equivalence testing with conditional samples }} ''This is a continuation of this previous open problem...") |
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| + | (This is a continuation of [[Open_Problems:66|Problem 66]] from the [[Workshops:Bertinoro_2014|2014 Bertinoro Workshop on Sublinear Algorithms]].) | ||
| − | + | For constant $\varepsilon>0$, it is known that the sample complexity of equivalence testing, in the conditional oracle model where the algorithm gets to condition the samples it receives on arbitrary subsets of the domain $[n]$, is $\Omega(\sqrt{\log\log n})$ and $O({\log\log n})$ {{cite|AcharyaCK-14,FalahatgarJOPS-15}}. | |
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| − | For constant $\varepsilon>0$ it is known that the sample complexity of equivalence testing, in the conditional oracle model where the algorithm gets to condition the samples it receives on arbitrary subsets of the domain $[n]$, is $\Omega(\sqrt{\log\log n})$ and $O({\log\log n})$ | ||
What is the exact dependence on the domain size of the sample complexity of equivalence testing in the conditional oracle model? | What is the exact dependence on the domain size of the sample complexity of equivalence testing in the conditional oracle model? | ||
Latest revision as of 16:05, 8 November 2017
| Suggested by | Jayadev Acharya |
|---|---|
| Source | FOCS 2017 |
| Short link | https://sublinear.info/87 |
(This is a continuation of Problem 66 from the 2014 Bertinoro Workshop on Sublinear Algorithms.)
For constant $\varepsilon>0$, it is known that the sample complexity of equivalence testing, in the conditional oracle model where the algorithm gets to condition the samples it receives on arbitrary subsets of the domain $[n]$, is $\Omega(\sqrt{\log\log n})$ and $O({\log\log n})$ [AcharyaCK-14,FalahatgarJOPS-15].
What is the exact dependence on the domain size of the sample complexity of equivalence testing in the conditional oracle model?
