English
Related papers

Related papers: Targeted Pseudorandom Generators, Simulation Advic…

200 papers

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

Pseudorandomness has played a central role in modern cryptography, finding theoretical and practical applications to various fields of computer science. A function that generates pseudorandom strings from shorter but truly random seeds is…

Formal Languages and Automata Theory · Computer Science 2016-10-25 Tomoyuki Yamakami

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

Let $\mathcal{L}$ be a language that can be decided in linear space and let $\epsilon >0$ be any constant. Let $\mathcal{A}$ be the exponential hardness assumption that for every $n$, membership in $\mathcal{L}$ for inputs of length~$n$…

Computational Complexity · Computer Science 2023-03-30 Edward Pyne , Ran Raz , Wei Zhan

The problem of constructing pseudorandom generators that fool halfspaces has been studied intensively in recent times. For fooling halfspaces over the hypercube with polynomially small error, the best construction known requires seed-length…

Computational Complexity · Computer Science 2014-11-18 Parikshit Gopalan , Daniel Kane , Raghu Meka

A curious property of randomized log-space search algorithms is that their outputs are often longer than their workspace. This leads to the question: how can we reproduce the results of a randomized log space computation without storing the…

Computational Complexity · Computer Science 2018-03-14 Ofer Grossman , Yang P. Liu

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

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 revisit Nisan's classical pseudorandom generator (PRG) for space-bounded computation (STOC 1990) and its applications in streaming algorithms. We describe a new generator, HashPRG, that can be thought of as a symmetric version of Nisan's…

Data Structures and Algorithms · Computer Science 2024-01-05 Praneeth Kacham , Rasmus Pagh , Mikkel Thorup , David P. Woodruff

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

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

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

We study weighted pseudorandom generators (WPRGs) and derandomizations for read-once branching programs (ROBPs). Denote $n$ and $w$ as the length and the width of a ROBP. We have the following results. For standard ROBPs, we give an…

Computational Complexity · Computer Science 2025-07-22 Kuan Cheng , Ruiyang Wu

A central approach to algorithmic derandomization is to construct probability distributions with small support that "fool" randomized algorithms, often enabling efficient parallel (NC) implementations. An abstraction of this idea is fooling…

Data Structures and Algorithms · Computer Science 2026-01-27 Jeff Giliberti , David G. Harris

We construct pseudorandom generators of seed length $\tilde{O}(\log(n)\cdot \log(1/\epsilon))$ that $\epsilon$-fool ordered read-once branching programs (ROBPs) of width $3$ and length $n$. For unordered ROBPs, we construct pseudorandom…

Computational Complexity · Computer Science 2018-06-13 Raghu Meka , Omer Reingold , Avishay Tal

We obtain new explicit pseudorandom generators for several computational models involving groups. Our main results are as follows: 1. We consider read-once group-products over a finite group $G$, i.e., tests of the form $\prod_{i=1}^n…

Computational Complexity · Computer Science 2025-06-05 Chin Ho Lee , Emanuele Viola

Despite their growing capabilities, language models still frequently reproduce content from their training data, generate repetitive text, and favor common grammatical patterns and vocabulary. A possible cause is the decoding strategy: the…

Computation and Language · Computer Science 2026-01-15 Giorgio Franceschelli , Mirco Musolesi

We develop techniques to prove lower bounds for the BCAST(log n) Broadcast Congested Clique model (a distributed message passing model where in each round, each processor can broadcast an O(log n)-sized message to all other processors). Our…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-05-21 Lijie Chen , Ofer Grossman

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

The hardness vs.~randomness paradigm aims to explicitly construct pseudorandom generators $G:\{0,1\}^r \rightarrow \{0,1\}^m$ that fool circuits of size $m$, assuming the existence of explicit hard functions. A ``high-end PRG'' with seed…

Computational Complexity · Computer Science 2023-11-21 Ronen Shaltiel , Emanuele Viola
‹ Prev 1 2 3 10 Next ›