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An optimal anytime estimation algorithm
dc.contributor.author | Gavaldà Mestre, Ricard |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics |
dc.date.accessioned | 2016-05-23T14:19:52Z |
dc.date.available | 2016-05-23T14:19:52Z |
dc.date.issued | 2004-12 |
dc.identifier.citation | Gavaldà, R. "An optimal anytime estimation algorithm". 2004. |
dc.identifier.uri | http://hdl.handle.net/2117/87244 |
dc.description.abstract | In many applications a key step is estimating some unknown quantity ~$mu$ from a sequence of trials, each having expected value~$mu$. Optimal algorithms are known when the task is to estimate $mu$ within a multiplicative factor of $epsilon$, for an $epsilon$ given in advance. In this paper we consider {em anytime} approximation algorithms, i.e., algorithms that must give a reliable approximation after each trial, and whose approximations have to be increasingly accurate as the number of trials grows. We give an anytime algorithm for this task when the only a-priori known property of $mu$ is its range, and show that it is asymptotically optimal in some cases, in the sense that no correct anytime algorithm can give asymptotically better approximations. The key ingredient is a new large deviation bound for the supremum of the deviations in an infinite sequence of trials, which can be seen as a non-limit analog of the classical Law of the Iterated Logarithm. |
dc.format.extent | 26 p. |
dc.language.iso | eng |
dc.relation.ispartofseries | LSI-04-56-R |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica |
dc.subject.other | Optimal algorithms |
dc.subject.other | Approximation algorithms |
dc.title | An optimal anytime estimation algorithm |
dc.type | External research report |
dc.contributor.group | Universitat Politècnica de Catalunya. LARCA - Laboratori d'Algorísmia Relacional, Complexitat i Aprenentatge |
dc.rights.access | Open Access |
local.identifier.drac | 18533123 |
dc.description.version | Postprint (published version) |
local.citation.author | Gavaldà, R. |
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