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Related papers: Lower Bounds for Convexity Testing

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We establish new upper and lower bounds on the number of queries required to test convexity of functions over various discrete domains. 1. We provide a simplified version of the non-adaptive convexity tester on the line. We re-prove the…

Computational Complexity · Computer Science 2019-08-08 Aleksandrs Belovs , Eric Blais , Abhinav Bommireddi

In the problem of high-dimensional convexity testing, there is an unknown set $S \subseteq \mathbb{R}^n$ which is promised to be either convex or $\varepsilon$-far from every convex body with respect to the standard multivariate normal…

Computational Complexity · Computer Science 2017-06-29 Xi Chen , Adam Freilich , Rocco A. Servedio , Timothy Sun

We consider the problem of Clifford testing, which asks whether a black-box $n$-qubit unitary is a Clifford unitary or at least $\varepsilon$-far from every Clifford unitary. We give the first 4-query Clifford tester, which decides this…

Quantum Physics · Physics 2025-10-09 Marcel Hinsche , Zongbo Bao , Philippe van Dordrecht , Jens Eisert , Jop Briët , Jonas Helsen

We show that for any constant $c>0$, any (two-sided error) adaptive algorithm for testing monotonicity of Boolean functions must have query complexity $\Omega(n^{1/2-c})$. This improves the $\tilde\Omega(n^{1/3})$ lower bound of [CWX17] and…

Computational Complexity · Computer Science 2025-11-10 Mark Chen , Xi Chen , Hao Cui , William Pires , Jonah Stockwell

We prove a lower bound of $\Omega(n^{1/2 - c})$, for all $c>0$, on the query complexity of (two-sided error) non-adaptive algorithms for testing whether an $n$-variable Boolean function is monotone versus constant-far from monotone. This…

Computational Complexity · Computer Science 2014-12-19 Xi Chen , Anindya De , Rocco A. Servedio , Li-Yang Tan

In this work, we develop new insights into the fundamental problem of convexity testing of real-valued functions over the domain $[n]$. Specifically, we present a nonadaptive algorithm that, given inputs $\eps \in (0,1), s \in \mathbb{N}$,…

Data Structures and Algorithms · Computer Science 2021-10-26 Abhiruk Lahiri , Ilan Newman , Nithin Varma

We show that every algorithm for testing $n$-variate Boolean functions for monotonicity must have query complexity $\tilde{\Omega}(n^{1/4})$. All previous lower bounds for this problem were designed for non-adaptive algorithms and, as a…

Computational Complexity · Computer Science 2015-11-17 Aleksandrs Belovs , Eric Blais

We study property testing of directed acyclicity in the unidirectional bounded-degree oracle model, where a query to a vertex reveals its outgoing neighbors. We prove that there exist absolute constants $d_0\in\mathbb{N}$ and…

Data Structures and Algorithms · Computer Science 2026-04-16 Yuichi Yoshida

We prove a $k^{-\Omega(\log(\varepsilon_2 - \varepsilon_1))}$ lower bound for adaptively testing whether a Boolean function is $\varepsilon_1$-close to or $\varepsilon_2$-far from $k$-juntas. Our results provide the first superpolynomial…

Data Structures and Algorithms · Computer Science 2023-04-24 Xi Chen , Shyamal Patel

We give the first super-polynomial (in fact, mildly exponential) lower bounds for tolerant testing (equivalently, distance estimation) of monotonicity, unateness, and juntas with a constant separation between the "yes" and "no" cases.…

Computational Complexity · Computer Science 2023-09-25 Xi Chen , Anindya De , Yuhao Li , Shivam Nadimpalli , Rocco A. Servedio

We give an adaptive algorithm which tests whether an unknown Boolean function $f\colon \{0, 1\}^n \to\{0, 1\}$ is unate, i.e. every variable of $f$ is either non-decreasing or non-increasing, or $\epsilon$-far from unate with one-sided…

Computational Complexity · Computer Science 2017-08-22 Xi Chen , Erik Waingarten , Jinyu Xie

Khot and Shinkar (RANDOM, 2016) recently describe an adaptive, $O(n \log(n)/\varepsilon)$-query tester for unateness of Boolean functions $f:\{0,1\}^n \to \{0,1\}$. In this note we describe a simple non-adaptive, $O(n…

Data Structures and Algorithms · Computer Science 2016-09-06 Deeparnab Chakrabarty , C. Seshadhri

We consider the problem of testing whether an unknown Boolean function $f$ is monotone versus $\epsilon$-far from every monotone function. The two main results of this paper are a new lower bound and a new algorithm for this well-studied…

Computational Complexity · Computer Science 2014-12-19 Xi Chen , Rocco A. Servedio , Li-Yang Tan

We improve both upper and lower bounds for the distribution-free testing of monotone conjunctions. Given oracle access to an unknown Boolean function $f:\{0,1\}^n \rightarrow \{0,1\}$ and sampling oracle access to an unknown distribution…

Discrete Mathematics · Computer Science 2015-11-12 Xi Chen , Jinyu Xie

We introduce a new model for testing graph properties which we call the \emph{rejection sampling model}. We show that testing bipartiteness of $n$-nodes graphs using rejection sampling queries requires complexity $\widetilde{\Omega}(n^2)$.…

Computational Complexity · Computer Science 2018-05-04 Amit Levi , Erik Waingarten

Let $X$ be a set of items of size $n$ , which may contain some defective items denoted by $I$, where $I \subseteq X$. In group testing, a {\it test} refers to a subset of items $Q \subset X$. The test outcome is $1$ (positive) if $Q$…

Data Structures and Algorithms · Computer Science 2023-09-19 Nader H. Bshouty , Gergely Harcos

The Huge Object model is a distribution testing model in which we are given access to independent samples from an unknown distribution over the set of strings $\{0,1\}^n$, but are only allowed to query a few bits from the samples. We…

Data Structures and Algorithms · Computer Science 2024-09-18 Tomer Adar , Eldar Fischer , Amit Levi

We give a $\mathrm{poly}(\log n, 1/\epsilon)$-query adaptive algorithm for testing whether an unknown Boolean function $f: \{-1,1\}^n \to \{-1,1\}$, which is promised to be a halfspace, is monotone versus $\epsilon$-far from monotone. Since…

Computational Complexity · Computer Science 2017-06-20 Xi Chen , Rocco A. Servedio , Li-Yang Tan , Erik Waingarten

The group testing problem consists of determining a small set of defective items from a larger set of items based on a number of possibly-noisy tests, and is relevant in applications such as medical testing, communication protocols, pattern…

Information Theory · Computer Science 2018-10-05 Jonathan Scarlett

Let $X$ be a set of items of size $n$ that contains some defective items, denoted by $I$, where $I \subseteq X$. In group testing, a {\it test} refers to a subset of items $Q \subset X$. The outcome of a test is $1$ if $Q$ contains at least…

Data Structures and Algorithms · Computer Science 2023-08-16 Nader H. Bshouty
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