Local correction of juntas
A Boolean function f over n variables is said to be q-locally correctable if, given a black-box access to a function g which is “close” to an isomorphism f σ of f, we can compute f σ ( x ) for any x ∈ Z 2 n with good probability using q queries to g. We observe that any k-junta, that is, any functio...
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Veröffentlicht in: | Information processing letters 2012-03, Vol.112 (6), p.223-226 |
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creator | Alon, Noga Weinstein, Amit |
description | A Boolean function
f over
n variables is said to be
q-locally correctable if, given a black-box access to a function
g which is “close” to an isomorphism
f
σ
of
f, we can compute
f
σ
(
x
)
for
any
x
∈
Z
2
n
with good probability using
q queries to
g.
We observe that any
k-junta, that is, any function which depends only on
k of its input variables, is
O
(
2
k
)
-locally correctable. Moreover, we show that there are examples where this is essentially best possible, and locally correcting some
k-juntas requires a number of queries which is exponential in
k. These examples, however, are far from being typical, and indeed we prove that for almost every
k-junta,
O
(
k
log
k
)
queries suffice.
► We consider the number of queries needed to locally correct
k-juntas. ► For every input
x, we must recover
f
(
x
)
with good probability using few queries to
f. ► We observe that for every
k-junta,
O
(
2
k
)
queries suffice for local correction. ► This is best possible as we show some
k-juntas require exponential number of queries. ► However, for most
k-juntas we provide an algorithm which performs
O
(
k
log
k
)
queries. |
doi_str_mv | 10.1016/j.ipl.2011.12.005 |
format | Article |
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f over
n variables is said to be
q-locally correctable if, given a black-box access to a function
g which is “close” to an isomorphism
f
σ
of
f, we can compute
f
σ
(
x
)
for
any
x
∈
Z
2
n
with good probability using
q queries to
g.
We observe that any
k-junta, that is, any function which depends only on
k of its input variables, is
O
(
2
k
)
-locally correctable. Moreover, we show that there are examples where this is essentially best possible, and locally correcting some
k-juntas requires a number of queries which is exponential in
k. These examples, however, are far from being typical, and indeed we prove that for almost every
k-junta,
O
(
k
log
k
)
queries suffice.
► We consider the number of queries needed to locally correct
k-juntas. ► For every input
x, we must recover
f
(
x
)
with good probability using few queries to
f. ► We observe that for every
k-junta,
O
(
2
k
)
queries suffice for local correction. ► This is best possible as we show some
k-juntas require exponential number of queries. ► However, for most
k-juntas we provide an algorithm which performs
O
(
k
log
k
)
queries.</description><identifier>ISSN: 0020-0190</identifier><identifier>EISSN: 1872-6119</identifier><identifier>DOI: 10.1016/j.ipl.2011.12.005</identifier><identifier>CODEN: IFPLAT</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Boolean functions ; Information processing ; Information retrieval ; Isomorphism ; Local correction ; Locally correctable codes ; Mathematical analysis ; Mathematical models ; Optimization algorithms ; Queries ; Randomized algorithms ; Studies</subject><ispartof>Information processing letters, 2012-03, Vol.112 (6), p.223-226</ispartof><rights>2011 Elsevier B.V.</rights><rights>Copyright Elsevier Sequoia S.A. Mar 15, 2012</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c400t-986c90f2ce775b6c584bb9908623cf04bbb8cacffdf24c93d9cab97a8d9bffe03</citedby><cites>FETCH-LOGICAL-c400t-986c90f2ce775b6c584bb9908623cf04bbb8cacffdf24c93d9cab97a8d9bffe03</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0020019011003279$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids></links><search><creatorcontrib>Alon, Noga</creatorcontrib><creatorcontrib>Weinstein, Amit</creatorcontrib><title>Local correction of juntas</title><title>Information processing letters</title><description>A Boolean function
f over
n variables is said to be
q-locally correctable if, given a black-box access to a function
g which is “close” to an isomorphism
f
σ
of
f, we can compute
f
σ
(
x
)
for
any
x
∈
Z
2
n
with good probability using
q queries to
g.
We observe that any
k-junta, that is, any function which depends only on
k of its input variables, is
O
(
2
k
)
-locally correctable. Moreover, we show that there are examples where this is essentially best possible, and locally correcting some
k-juntas requires a number of queries which is exponential in
k. These examples, however, are far from being typical, and indeed we prove that for almost every
k-junta,
O
(
k
log
k
)
queries suffice.
► We consider the number of queries needed to locally correct
k-juntas. ► For every input
x, we must recover
f
(
x
)
with good probability using few queries to
f. ► We observe that for every
k-junta,
O
(
2
k
)
queries suffice for local correction. ► This is best possible as we show some
k-juntas require exponential number of queries. ► However, for most
k-juntas we provide an algorithm which performs
O
(
k
log
k
)
queries.</description><subject>Boolean functions</subject><subject>Information processing</subject><subject>Information retrieval</subject><subject>Isomorphism</subject><subject>Local correction</subject><subject>Locally correctable codes</subject><subject>Mathematical analysis</subject><subject>Mathematical models</subject><subject>Optimization algorithms</subject><subject>Queries</subject><subject>Randomized algorithms</subject><subject>Studies</subject><issn>0020-0190</issn><issn>1872-6119</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><recordid>eNp9kE1LxDAQhoMouK7-AD0tnry0zqTbNMGTiF-w4EXPIZ0mkNJt1qQV_PdmWU8ePA0Dz_sy8zB2iVAioLjtS78bSg6IJfISoD5iC5QNLwSiOmYLAA4FoIJTdpZSDwBiXTULdrUJZIYVhRgtTT6Mq-BW_TxOJp2zE2eGZC9-55J9PD2-P7wUm7fn14f7TUFrgKlQUpACx8k2Td0KquW6bZUCKXhFDvLSSjLkXOf4mlTVKTKtaozsVOuchWrJbg69uxg-Z5smvfWJ7DCY0YY5aRQNViiVaDJ6_QftwxzHfJ1WWEuEBusM4QGiGFKK1uld9FsTvzWC3svSvc6y9F6WRq6zrJy5O2RsfvTL26gTeTuS7fzei-6C_yf9A2wccHc</recordid><startdate>20120315</startdate><enddate>20120315</enddate><creator>Alon, Noga</creator><creator>Weinstein, Amit</creator><general>Elsevier B.V</general><general>Elsevier Sequoia S.A</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20120315</creationdate><title>Local correction of juntas</title><author>Alon, Noga ; Weinstein, Amit</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c400t-986c90f2ce775b6c584bb9908623cf04bbb8cacffdf24c93d9cab97a8d9bffe03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Boolean functions</topic><topic>Information processing</topic><topic>Information retrieval</topic><topic>Isomorphism</topic><topic>Local correction</topic><topic>Locally correctable codes</topic><topic>Mathematical analysis</topic><topic>Mathematical models</topic><topic>Optimization algorithms</topic><topic>Queries</topic><topic>Randomized algorithms</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Alon, Noga</creatorcontrib><creatorcontrib>Weinstein, Amit</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Information processing letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Alon, Noga</au><au>Weinstein, Amit</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Local correction of juntas</atitle><jtitle>Information processing letters</jtitle><date>2012-03-15</date><risdate>2012</risdate><volume>112</volume><issue>6</issue><spage>223</spage><epage>226</epage><pages>223-226</pages><issn>0020-0190</issn><eissn>1872-6119</eissn><coden>IFPLAT</coden><abstract>A Boolean function
f over
n variables is said to be
q-locally correctable if, given a black-box access to a function
g which is “close” to an isomorphism
f
σ
of
f, we can compute
f
σ
(
x
)
for
any
x
∈
Z
2
n
with good probability using
q queries to
g.
We observe that any
k-junta, that is, any function which depends only on
k of its input variables, is
O
(
2
k
)
-locally correctable. Moreover, we show that there are examples where this is essentially best possible, and locally correcting some
k-juntas requires a number of queries which is exponential in
k. These examples, however, are far from being typical, and indeed we prove that for almost every
k-junta,
O
(
k
log
k
)
queries suffice.
► We consider the number of queries needed to locally correct
k-juntas. ► For every input
x, we must recover
f
(
x
)
with good probability using few queries to
f. ► We observe that for every
k-junta,
O
(
2
k
)
queries suffice for local correction. ► This is best possible as we show some
k-juntas require exponential number of queries. ► However, for most
k-juntas we provide an algorithm which performs
O
(
k
log
k
)
queries.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/j.ipl.2011.12.005</doi><tpages>4</tpages><oa>free_for_read</oa></addata></record> |
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issn | 0020-0190 1872-6119 |
language | eng |
recordid | cdi_proquest_miscellaneous_1671318967 |
source | Elsevier ScienceDirect Journals |
subjects | Boolean functions Information processing Information retrieval Isomorphism Local correction Locally correctable codes Mathematical analysis Mathematical models Optimization algorithms Queries Randomized algorithms Studies |
title | Local correction of juntas |
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