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We study Boolean circuits as a representation of Boolean functions and consider different equivalence, audit, and enumeration problems. For a number of restricted sets of gate types (bases) we obtain efficient algorithms, while for all…

Computational Complexity · Computer Science 2015-07-01 Elmar Böhler , Nadia Creignou , Matthias Galota , Steffen Reith , Henning Schnoor , Heribert Vollmer

In this paper, we initiate study of the computational power of adaptive and non-adaptive monotone decision trees - decision trees where each query is a monotone function on the input bits. In the most general setting, the monotone decision…

Computational Complexity · Computer Science 2023-01-03 Prashanth Amireddy , Sai Jayasurya , Jayalal Sarma

We show that a certain tensor norm, the completely bounded norm, can be expressed by a semidefinite program. This tensor norm recently attracted attention in the field of quantum computing, where it was used by Arunachalam, Bri\"{e}t and…

Quantum Physics · Physics 2019-01-16 Sander Gribling , Monique Laurent

We study minimum-error identification of an unknown single-bit Boolean function given black-box (oracle) access with one allowed query. Rather than stopping at an abstract optimal measurement, we give a fully constructive solution: an…

Quantum Physics · Physics 2025-12-19 Leonardo Bohac

In this note we compare two measures of the complexity of a class $\mathcal F$ of Boolean functions studied in (unconditional) pseudorandomness: $\mathcal F$'s ability to distinguish between biased and uniform coins (the coin problem), and…

Computational Complexity · Computer Science 2020-09-01 Rohit Agrawal

In unitary property testing a quantum algorithm, also known as a tester, is given query access to a black-box unitary and has to decide whether it satisfies some property. We propose a new technique for proving lower bounds on the quantum…

Quantum Physics · Physics 2025-04-23 Jordi Weggemans

$\newcommand{\sp}{\mathsf{sparsity}}\newcommand{\s}{\mathsf{s}}\newcommand{\al}{\mathsf{alt}}$ The well-known Sensitivity Conjecture states that for any Boolean function $f$, block sensitivity of $f$ is at most polynomial in sensitivity of…

Computational Complexity · Computer Science 2019-02-12 Krishnamoorthy Dinesh , Jayalal Sarma

In this paper, we introduce the hybrid query complexity, denoted as $\mathrm{Q}(f;q)$, which is the minimal query number needed to compute $f$, when a classical decision tree is allowed to call $q'$-query quantum subroutines for any $q'\leq…

Computational Complexity · Computer Science 2019-12-02 Xiaoming Sun , Yufan Zheng

Let $\R(\cdot)$ stand for the bounded-error randomized query complexity. We show that for any relation $f \subseteq \{0,1\}^n \times \mathcal{S}$ and partial Boolean function $g \subseteq \{0,1\}^n \times \{0,1\}$, $\R_{1/3}(f \circ g^n) =…

Computational Complexity · Computer Science 2018-01-11 Swagato Sanyal

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

Many problems in interprocedural program analysis can be modeled as the context-free language (CFL) reachability problem on graphs and can be solved in cubic time. Despite years of efforts, there are no known truly sub-cubic algorithms for…

Formal Languages and Automata Theory · Computer Science 2021-02-26 Dmitry Chistikov , Rupak Majumdar , Philipp Schepper

While on some natural distributions, neural-networks are trained efficiently using gradient-based algorithms, it is known that learning them is computationally hard in the worst-case. To separate hard from easy to learn distributions, we…

Machine Learning · Computer Science 2020-01-22 Eran Malach , Shai Shalev-Shwartz

We consider the quantum complexities of the following three problems: searching an ordered list, sorting an un-ordered list, and deciding whether the numbers in a list are all distinct. Letting N be the number of elements in the input list,…

Quantum Physics · Physics 2016-12-30 Peter Hoyer , Jan Neerbek , Yaoyun Shi

In the noisy query model, the (binary) return value of every query (possibly repeated) is independently flipped with some fixed probability $p \in (0, 1/2)$. In this paper, we obtain tight bounds on the noisy query complexity of several…

Data Structures and Algorithms · Computer Science 2025-02-17 Yuzhou Gu , Xin Li , Yinzhan Xu

We study classical query algorithms with post-selection, and find that they are closely connected to rational functions with nonnegative coefficients. We show that the post-selected classical query complexity of a Boolean function is equal…

Computational Complexity · Computer Science 2018-05-15 Chris Cade

This work investigates the oracle separation between the physically motivated complexity class of noisy quantum circuits, inspired by definitions such as those presented by Chen, Cotler, Huang, and Li (2022). We establish that with a…

Quantum Physics · Physics 2024-05-15 Nai-Hui Chia , Min-Hsiu Hsieh , Shih-Han Hung , En-Jui Kuo

We study the relationship between various one-way communication complexity measures of a composed function with the analogous decision tree complexity of the outer function. We consider two gadgets: the AND function on 2 inputs, and the…

Computational Complexity · Computer Science 2022-01-19 Nikhil S. Mande , Swagato Sanyal , Suhail Sherif

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

Inspired by Solomonoffs theory of inductive inference, we propose a prior based on circuit complexity. There are several advantages to this approach. First, it relies on a complexity measure that does not depend on the choice of UTM. There…

Machine Learning · Computer Science 2023-06-27 Cole Wyeth , Carl Sturtivant

While neural networks have achieved high performance in different learning tasks, their accuracy drops significantly in the presence of small adversarial perturbations to inputs. Defenses based on regularization and adversarial training are…

Machine Learning · Computer Science 2019-02-07 Sahil Singla , Soheil Feizi
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