TY - GEN
T1 - Testing local properties of arrays
AU - Ben-Eliezer, Omri
N1 - Publisher Copyright:
© Omri Ben-Eliezer.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - We study testing of local properties in one-dimensional and multi-dimensional arrays. A property of d-dimensional arrays f : [n]d → Σ is k-local if it can be defined by a family of k x . . . x k forbidden consecutive patterns. This definition captures numerous interesting properties. For example, monotonicity, Lipschitz continuity and submodularity are 2-local; convexity is (usually) 3-local; and many typical problems in computational biology and computer vision involve o(n)local properties. In this work, we present a generic approach to test all local properties of arrays over any finite (and not necessarily bounded size) alphabet. We show that any k-local property of ddimensional arrays is testable by a simple canonical one-sided error non-adaptive ϵ-test, whose query complexity is O(ϵ−1k log ϵn/k ) for d = 1 and O(cdϵ−1/dk · nd−1) for d > 1. The queries made by the canonical test constitute sphere-like structures of varying sizes, and are completely independent of the property and the alphabet Σ. The query complexity is optimal for a wide range of parameters: For d = 1, this matches the query complexity of many previously investigated local properties, while for d > 1 we design and analyze new constructions of k-local properties whose one-sided non-adaptive query complexity matches our upper bounds. For some previously studied properties, our method provides the first known sublinear upper bound on the query complexity.
AB - We study testing of local properties in one-dimensional and multi-dimensional arrays. A property of d-dimensional arrays f : [n]d → Σ is k-local if it can be defined by a family of k x . . . x k forbidden consecutive patterns. This definition captures numerous interesting properties. For example, monotonicity, Lipschitz continuity and submodularity are 2-local; convexity is (usually) 3-local; and many typical problems in computational biology and computer vision involve o(n)local properties. In this work, we present a generic approach to test all local properties of arrays over any finite (and not necessarily bounded size) alphabet. We show that any k-local property of ddimensional arrays is testable by a simple canonical one-sided error non-adaptive ϵ-test, whose query complexity is O(ϵ−1k log ϵn/k ) for d = 1 and O(cdϵ−1/dk · nd−1) for d > 1. The queries made by the canonical test constitute sphere-like structures of varying sizes, and are completely independent of the property and the alphabet Σ. The query complexity is optimal for a wide range of parameters: For d = 1, this matches the query complexity of many previously investigated local properties, while for d > 1 we design and analyze new constructions of k-local properties whose one-sided non-adaptive query complexity matches our upper bounds. For some previously studied properties, our method provides the first known sublinear upper bound on the query complexity.
KW - Hypergrid
KW - Local properties
KW - Monotonicity testing
KW - Pattern matching
KW - Property testing
UR - http://www.scopus.com/inward/record.url?scp=85069498771&partnerID=8YFLogxK
U2 - 10.4230/LIPIcs.ITCS.2019.11
DO - 10.4230/LIPIcs.ITCS.2019.11
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AN - SCOPUS:85069498771
T3 - Leibniz International Proceedings in Informatics, LIPIcs
BT - 10th Innovations in Theoretical Computer Science, ITCS 2019
A2 - Blum, Avrim
PB - Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
T2 - 10th Innovations in Theoretical Computer Science, ITCS 2019
Y2 - 10 January 2019 through 12 January 2019
ER -