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Kabir Peshawaria

dblp:420/0956 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2026
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Computational complexity · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational complexity › property testing
boolean function testing
1.012026
Relative-Error Unateness Testing · ICALP 2026
Computational complexity
lower bounds
1.012026
Relative-Error Unateness Testing · ICALP 2026
Computational complexity
property testing
1.012026
Relative-Error Unateness Testing · ICALP 2026
Computational complexity › property testing
property testing lower bounds
1.012026
Relative-Error Unateness Testing · ICALP 2026
Computational complexity › property testing › boolean function testing
unateness testing
1.012026
Relative-Error Unateness Testing · ICALP 2026
YearPublicationVenuePosition
2026 Relative-Error Unateness Testing
abstract
The model of relative-error property testing of Boolean functions has been the subject of significant recent research effort [X. Chen et al., 2025; Chen et al., 2025; Chen et al., 2025]. In this paper we consider the problem of relative-error testing an unknown and arbitrary f: {0,1}ⁿ → {0,1} for the property of being a unate function, i.e. a function that is either monotone non-increasing or monotone non-decreasing in each of the n input variables. Our first result is a one-sided non-adaptive algorithm for this problem that makes Õ(log(N)/ε) samples and queries, where N = |f^{-1}(1)| is the number of satisfying assignments of the function that is being tested and the value of N is given as an input parameter to the algorithm. Building on this algorithm, we next give a one-sided adaptive algorithm for this problem that does not need to be given the value of N and with high probability makes Õ(log(N)/ε) samples and queries. We also give lower bounds for both adaptive and non-adaptive two-sided algorithms that are given the value of N up to a constant multiplicative factor. In the non-adaptive case, our lower bounds essentially match the complexity of the algorithm that we provide.
Xi Chen 0001, Diptaksho Palit, Kabir Peshawaria, William Pires, Rocco A. Servedio
ICALP3