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We develop a pseudo-random generator to fool degree-$d$ polynomial threshold functions with respect to the Gaussian distribution. For $c>0$ any constant, we construct a pseudo-random generator that fools such functions to within $\epsilon$…

Computational Complexity · Computer Science 2011-04-08 Daniel M. Kane

We develop a pseudorandom generator that fools degree-$d$ polynomial threshold functions in $n$ variables with respect to the Gaussian distribution and has seed length $O_{c,d}(\log(n) \epsilon^{-c})$.

Computational Complexity · Computer Science 2012-10-05 Daniel M. Kane

Developing explicit pseudorandom generators (PRGs) for prominent categories of Boolean functions is a key focus in computational complexity theory. In this paper, we investigate the PRGs against the functions of degree-$d$ polynomial…

Computational Complexity · Computer Science 2025-04-22 Penghui Yao , Mingnan Zhao

We study the natural question of constructing pseudorandom generators (PRGs) for low-degree polynomial threshold functions (PTFs). We give a PRG with seed-length log n/eps^{O(d)} fooling degree d PTFs with error at most eps. Previously, no…

Computational Complexity · Computer Science 2015-03-13 Raghu Meka , David Zuckerman

A polynomial threshold function (PTF) $f:\mathbb{R}^n \rightarrow \mathbb{R}$ is a function of the form $f(x) = \mathsf{sign}(p(x))$ where $p$ is a polynomial of degree at most $d$. PTFs are a classical and well-studied complexity class…

Computational Complexity · Computer Science 2021-11-30 Zander Kelley , Raghu Meka

We present a new approach to constructing unconditional pseudorandom generators against classes of functions that involve computing a linear function of the inputs. We give an explicit construction of a pseudorandom generator that fools the…

Computational Complexity · Computer Science 2015-11-19 Parikshit Gopalan , Daniel Kane , Raghu Meka

Halfspaces or linear threshold functions are widely studied in complexity theory, learning theory and algorithm design. In this work we study the natural problem of constructing pseudorandom generators (PRGs) for halfspaces over the sphere,…

Computational Complexity · Computer Science 2015-03-30 Pravesh Kothari , Raghu Meka

We give a pseudorandom generator that fools degree-$d$ polynomial threshold functions over $n$-dimensional Gaussian space with seed length $\mathrm{poly}(d)\cdot \log n$. All previous generators had a seed length with at least a $2^d$…

Computational Complexity · Computer Science 2022-02-10 Ryan O'Donnell , Rocco A. Servedio , Li-Yang Tan , Daniel Kane

We show a new PRG construction fooling depth-$d$, size-$m$ $\mathsf{AC}^0$ circuits within error $\varepsilon$, which has seed length $O(\log^{d-1}(m)\log(m/\varepsilon)\log\log(m))$. Our PRG improves on previous work (Trevisan and Xue…

Computational Complexity · Computer Science 2023-01-25 Xin Lyu

We give improved pseudorandom generators (PRGs) for Lipschitz functions of low-degree polynomials over the hypercube. These are functions of the form psi(P(x)), where P is a low-degree polynomial and psi is a function with small Lipschitz…

Computational Complexity · Computer Science 2012-11-07 Daniel Kane , Raghu Meka

We prove new results on the polarizing random walk framework introduced in recent works of Chattopadhyay {et al.} [CHHL19,CHLT19] that exploit $L_1$ Fourier tail bounds for classes of Boolean functions to construct pseudorandom generators…

Computational Complexity · Computer Science 2020-11-10 Eshan Chattopadhyay , Jason Gaitonde , Chin Ho Lee , Shachar Lovett , Abhishek Shetty

We study the computational power of polynomial threshold functions, that is, threshold functions of real polynomials over the boolean cube. We provide two new results bounding the computational power of this model. Our first result shows…

Computational Complexity · Computer Science 2009-11-29 Ido Ben-Eliezer , Shachar Lovett , Ariel Yadin

We establish new correlation bounds and pseudorandom generators for a collection of computation models. These models are all natural generalizations of structured low-degree $F_2$-polynomials that we did not have correlation bounds for…

Computational Complexity · Computer Science 2025-01-07 Vinayak M. Kumar

Pseudorandom generators (PRGs) for low-degree polynomials are a central object in pseudorandomness, with applications to circuit lower bounds and derandomization. Viola's celebrated construction gives a PRG over the binary field, but with…

Computational Complexity · Computer Science 2026-02-11 Gil Cohen , Dean Doron , Noam Goldgraber

We give the best known pseudorandom generators for two touchstone classes in unconditional derandomization: an $\varepsilon$-PRG for the class of size-$M$ depth-$d$ $\mathsf{AC}^0$ circuits with seed length $\log(M)^{d+O(1)}\cdot…

Computational Complexity · Computer Science 2018-01-12 Rocco A. Servedio , Li-Yang Tan

We present an iterative approach to constructing pseudorandom generators, based on the repeated application of mild pseudorandom restrictions. We use this template to construct pseudorandom generators for combinatorial rectangles and…

Computational Complexity · Computer Science 2012-10-02 Parikshit Gopalan , Raghu Meka , Omer Reingold , Luca Trevisan , Salil Vadhan

A sliding-window algorithm of window size $t$ is an algorithm whose current operation depends solely on the last $t$ symbols read. We construct pseudorandom generators (PRGs) for low-space randomized sliding-window algorithms that have…

Computational Complexity · Computer Science 2023-01-19 Augusto Modanese

A select collection of pseudorandom number generators is applied to a Monte Carlo study of the two dimensional square site percolation model. A generator suitable for high precision calculations is identified from an application specific…

Disordered Systems and Neural Networks · Physics 2009-11-13 Michael J. Lee

A central question in derandomization is whether randomized logspace (RL) equals deterministic logspace (L). To show that RL=L, it suffices to construct explicit pseudorandom generators (PRGs) that fool polynomial-size read-once (oblivious)…

Computational Complexity · Computer Science 2018-08-21 Michael A. Forbes , Zander Kelley

We construct pseudorandom generators that fool functions of halfspaces (threshold functions) under a very broad class of product distributions. This class includes not only familiar cases such as the uniform distribution on the discrete…

Computational Complexity · Computer Science 2010-01-12 P. Gopalan , R. O'Donnell , Y. Wu , D. Zuckerman
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