TY - GEN
T1 - Almost optimal distribution-free junta testing
AU - Bshouty, Nader H.
N1 - Publisher Copyright: © Nader H. Bshouty; licensed under Creative Commons License CC-BY 34th Computational Complexity Conference (CCC 2019).
PY - 2019/7/1
Y1 - 2019/7/1
N2 - We consider the problem of testing whether an unknown n-variable Boolean function is a k-junta in the distribution-free property testing model, where the distance between functions is measured with respect to an arbitrary and unknown probability distribution over {0, 1}n. Chen, Liu, Servedio, Sheng and Xie [35] showed that the distribution-free k-junta testing can be performed, with one-sided error, by an adaptive algorithm that makes Õ(k2)/ queries. In this paper, we give a simple two-sided error adaptive algorithm that makes Õ(k/) queries.
AB - We consider the problem of testing whether an unknown n-variable Boolean function is a k-junta in the distribution-free property testing model, where the distance between functions is measured with respect to an arbitrary and unknown probability distribution over {0, 1}n. Chen, Liu, Servedio, Sheng and Xie [35] showed that the distribution-free k-junta testing can be performed, with one-sided error, by an adaptive algorithm that makes Õ(k2)/ queries. In this paper, we give a simple two-sided error adaptive algorithm that makes Õ(k/) queries.
KW - Distribution-free property testing
KW - K-Junta
UR - http://www.scopus.com/inward/record.url?scp=85070692292&partnerID=8YFLogxK
U2 - 10.4230/LIPIcs.CCC.2019.2
DO - 10.4230/LIPIcs.CCC.2019.2
M3 - منشور من مؤتمر
T3 - Leibniz International Proceedings in Informatics, LIPIcs
BT - 34th Computational Complexity Conference, CCC 2019
A2 - Shpilka, Amir
T2 - 34th Computational Complexity Conference, CCC 2019
Y2 - 18 July 2019 through 20 July 2019
ER -