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We show that there is a randomized algorithm that, when given a small constant-depth Boolean circuit $C$ made up of gates that compute constant-degree Polynomial Threshold functions or PTFs (i.e., Boolean functions that compute signs of…

Computational Complexity · Computer Science 2018-09-18 Swapnam Bajpai , Vaibhav Krishan , Deepanshu Kush , Nutan Limaye , Srikanth Srinivasan

Algorithmic tools for graphs of small treewidth are used to address questions in complexity theory. For both arithmetic and Boolean circuits, it is shown that any circuit of size $n^{O(1)}$ and treewidth $O(\log^i n)$ can be simulated by a…

Computational Complexity · Computer Science 2015-05-14 Maurice Jansen , Jayalal Sarma M. N

We prove that for every class $C$ of graphs with effectively bounded expansion, given a first-order sentence $\varphi$ and an $n$-element structure $\mathbb{A}$ whose Gaifman graph belongs to $C$, the question whether $\varphi$ holds in…

Discrete Mathematics · Computer Science 2018-05-10 Michał Pilipczuk , Sebastian Siebertz , Szymon Toruńczyk

A proof system for a language L is a function f such that Range(f) is exactly L. In this paper, we look at proofsystems from a circuit complexity point of view and study proof systems that are computationally very restricted. The…

Computational Complexity · Computer Science 2013-07-19 Andreas Krebs , Nutan Limaye , Meena Mahajan , Karteek Sreenivasaiah

Let $ACC \circ THR$ be the class of constant-depth circuits comprised of AND, OR, and MOD$m$ gates (for some constant $m > 1$), with a bottom layer of gates computing arbitrary linear threshold functions. This class of circuits can be seen…

Computational Complexity · Computer Science 2014-01-13 Ryan Williams

The past decade has seen a significant interest in learning tractable probabilistic representations. Arithmetic circuits (ACs) were among the first proposed tractable representations, with some subsequent representations being instances of…

Artificial Intelligence · Computer Science 2017-08-25 Arthur Choi , Adnan Darwiche

We generalize the "indirect learning" technique of Furst et. al., 1991 to reduce from learning a concept class over a samplable distribution $\mu$ to learning the same concept class over the uniform distribution. The reduction succeeds when…

Machine Learning · Computer Science 2021-12-24 Eric Binnendyk , Marco Carmosino , Antonina Kolokolova , Ramyaa Ramyaa , Manuel Sabin

We study the space of functions computed by random-layered machines, including deep neural networks and Boolean circuits. Investigating the distribution of Boolean functions computed on the recurrent and layer-dependent architectures, we…

Machine Learning · Computer Science 2020-10-15 Alexander Mozeika , Bo Li , David Saad

Using a proofs-as-programs correspondence, Terui was able to compare two models of parallel computation: Boolean circuits and proof nets for multiplicative linear logic. Mogbil et. al. gave a logspace translation allowing us to compare…

Computational Complexity · Computer Science 2012-01-06 Clément Aubert

Transformers have emerged as a widely used neural network model for various natural language processing tasks. Previous research explored their relationship with constant-depth threshold circuits, making two assumptions: average-hard…

Computation and Language · Computer Science 2023-08-23 Lena Strobl

The approximate degree of a Boolean function $f \colon \{-1, 1\}^n \rightarrow \{-1, 1\}$ is the least degree of a real polynomial that approximates $f$ pointwise to error at most $1/3$. We introduce a generic method for increasing the…

Computational Complexity · Computer Science 2017-03-20 Mark Bun , Justin Thaler

We show that if a language is recognized within certain error bounds by constant-depth quantum circuits over a finite family of gates, then it is computable in (classical) polynomial time. In particular, our results imply EQNC^0 is…

Quantum Physics · Physics 2007-05-23 Stephen Fenner , Frederic Green , Steven Homer , Yong Zhang

We say that a circuit $C$ over a field $F$ functionally computes an $n$-variate polynomial $P$ if for every $x \in \{0,1\}^n$ we have that $C(x) = P(x)$. This is in contrast to syntactically computing $P$, when $C \equiv P$ as formal…

Computational Complexity · Computer Science 2016-05-16 Michael A. Forbes , Mrinal Kumar , Ramprasad Saptharishi

The motivation for this paper is to study the complexity of constant-width arithmetic circuits. Our main results are the following. 1. For every k > 1, we provide an explicit polynomial that can be computed by a linear-sized monotone…

Computational Complexity · Computer Science 2009-08-14 V. Arvind , Pushkar S. Joglekar , Srikanth Srinivasan

We establish a generic form of hardness amplification for the approximability of constant-depth Boolean circuits by polynomials. Specifically, we show that if a Boolean circuit cannot be pointwise approximated by low-degree polynomials to…

Computational Complexity · Computer Science 2014-04-29 Mark Bun , Justin Thaler

A notorious open question in circuit complexity is whether Boolean operations of arbitrary arity can efficiently be expressed using modular counting gates only. H{\aa}stad's celebrated switching lemma yields exponential lower bounds for the…

Computational Complexity · Computer Science 2026-04-07 Benedikt Pago

The elementary arithmetic operations $+,\cdot,\le$ on integers are well-known to be computable in the weak complexity class $\mathrm{TC}^0$, and it is a basic question what properties of these operations can be proved using only…

Logic in Computer Science · Computer Science 2015-03-25 Emil Jeřábek

We consider boolean circuits computing n-operators f:{0,1}^n --> {0,1}^n. As gates we allow arbitrary boolean functions; neither fanin nor fanout of gates is restricted. An operator is linear if it computes n linear forms, that is, computes…

Computational Complexity · Computer Science 2015-03-17 S. Jukna , G. Schnitger

We present the first computationally-efficient algorithm for average-case learning of shallow quantum circuits with many-qubit gates. Specifically, we provide a quasi-polynomial time and sample complexity algorithm for learning unknown…

Quantum Physics · Physics 2025-06-11 Francisca Vasconcelos , Hsin-Yuan Huang

The threshold degree of a Boolean function $f\colon\{0,1\}^n\to\{0,1\}$ is the minimum degree of a real polynomial $p$ that represents $f$ in sign: $\mathrm{sgn}\; p(x)=(-1)^{f(x)}.$ A related notion is sign-rank, defined for a Boolean…

Computational Complexity · Computer Science 2019-01-07 Alexander A. Sherstov , Pei Wu