English
Related papers

Related papers: Improved pseudorandom generators from pseudorandom…

200 papers

Minimizing empirical risk subject to a set of constraints can be a useful strategy for learning restricted classes of functions, such as monotonic functions, submodular functions, classifiers that guarantee a certain class label for some…

Machine Learning · Computer Science 2016-10-26 Andrew Cotter , Maya Gupta , Jan Pfeifer

In this paper we present a new pseudorandom number generator (PRNG) on graphics processing units (GPU). This PRNG is based on the so-called chaotic iterations. It is firstly proven to be chaotic according to the Devaney's formulation. We…

Cryptography and Security · Computer Science 2011-12-23 Jacques M. Bahi , Raphaël Couturier , Christophe Guyeux , Pierre-Cyrille Héam

Generating random and pseudorandom numbers with a deterministic system is a long-standing challenge in theoretical research and engineering applications. Several pseudorandom number generators based on the inversive congruential method have…

Discrete Mathematics · Computer Science 2024-01-17 Xiaoxiong Lu , Chengqing Li , Bo Zhou

We design a deterministic subexponential time algorithm that takes as input a multivariate polynomial $f$ computed by a constant-depth circuit over rational numbers, and outputs a list $L$ of circuits (of unbounded depth and possibly with…

Computational Complexity · Computer Science 2024-03-05 Mrinal Kumar , Varun Ramanathan , Ramprasad Saptharishi , Ben Lee Volk

A new construction is proposed for low density parity check (LDPC) codes using quadratic permutation polynomials over finite integer rings. The associated graphs for the new codes have both algebraic and pseudo-random nature, and the new…

Information Theory · Computer Science 2007-07-13 Oscar Y. Takeshita

In this paper, we analyze the tradeoff between coding rate and asymptotic performance of a class of generalized low-density parity-check (GLDPC) codes constructed by including a certain fraction of generalized constraint (GC) nodes in the…

Information Theory · Computer Science 2019-10-16 Yanfang Liu , Pablo M. Olmos , Tobias Koch

Pseudo-random number generators are widely used in many branches of science, mainly in applications related to Monte Carlo methods, although they are deterministic in design and, therefore, unsuitable for tackling fundamental problems in…

We prove hardness-of-learning results under a well-studied assumption on the existence of local pseudorandom generators. As we show, this assumption allows us to surpass the current state of the art, and prove hardness of various basic…

Machine Learning · Computer Science 2021-06-09 Amit Daniely , Gal Vardi

A new class of nonparametric prior distributions, termed Beta-Binomial stick-breaking process, is proposed. By allowing the underlying length random variables to be dependent through a Beta marginals Markov chain, an appealing discrete…

Statistics Theory · Mathematics 2020-08-12 María F. Gil-Leyva , Ramsés H. Mena , Theodoros Nicoleris

Quantum Key Distribution(QKD) thrives to achieve perfect secrecy of One time Pad (OTP) through quantum processes. One of the crucial components of QKD are Quantum Random Number Generators(QRNG) for generation of keys. Unfortunately, these…

Cryptography and Security · Computer Science 2023-11-07 Arun Mishra , Kanaka Raju Pandiri , Anupama Arjun Pandit , Lucy Sharma

In this paper, we study the structure of set-multilinear arithmetic circuits and set-multilinear branching programs with the aim of showing lower bound results. We define some natural restrictions of these models for which we are able to…

Computational Complexity · Computer Science 2015-11-10 V. Arvind , S. Raja

By using the notion of $d$-embedding $\Gamma$ of a (canonical) subgeometry $\Sigma$ and of exterior set with respect to the $h$-secant variety $\Omega_{h}(\mathcal{A})$ of a subset $\mathcal{A}$, $ 0 \leq h \leq n-1$, in the finite…

Information Theory · Computer Science 2024-05-03 Nicola Durante , Giovanni Giuseppe Grimaldi , Giovanni Longobardi

We design new polynomials for representing threshold functions in three different regimes: probabilistic polynomials of low degree, which need far less randomness than previous constructions, polynomial threshold functions (PTFs) with…

Data Structures and Algorithms · Computer Science 2016-08-16 Josh Alman , Timothy M. Chan , Ryan Williams

In this paper, we study the problem of sampling from a given probability density function that is known to be smooth and strongly log-concave. We analyze several methods of approximate sampling based on discretizations of the (highly…

Statistics Theory · Mathematics 2024-02-26 Arnak S. Dalalyan , Avetik G. Karagulyan

We give a polynomial time algorithm to decode multivariate polynomial codes of degree $d$ up to half their minimum distance, when the evaluation points are an arbitrary product set $S^m$, for every $d < |S|$. Previously known algorithms can…

Computational Complexity · Computer Science 2015-11-25 John Kim , Swastik Kopparty

Pseudo-random number generators (PRNGs) play an important role to ensure the security and confidentiality of image cryptographic algorithms. Their primary function is to generate a sequence of numbers that possesses unpredictability and…

Cryptography and Security · Computer Science 2023-07-11 Takreem Haider , Saúl A. Blanco , Umar Hayat

The use of three extractors, fed by linear feedback shift registers (LFSR) for generating pseudo-random bit streams is investigated. Specifically, a standard LFSR is combined with a von Neumann extractor, a modified LFSR, extended by the…

Cryptography and Security · Computer Science 2024-04-19 Holger Nobach

We introduce the Collatz-Weyl Generators, a family of uniform pseudorandom number generators (PRNGs) which are based on generalized Collatz mappings, derived from the Collatz conjecture and Weyl sequences. The high-quality statistical…

Computational Engineering, Finance, and Science · Computer Science 2024-12-03 Tomasz R. Działa

A device-independent randomness expansion protocol aims to take an initial random string and generate a longer one, where the security of the protocol does not rely on knowing the inner workings of the devices used to run it. In order to do…

Quantum Physics · Physics 2026-01-06 Rutvij Bhavsar , Sammy Ragy , Roger Colbeck

Inference in discrete graphical models with variational methods is difficult because of the inability to re-parameterize gradients of the Evidence Lower Bound (ELBO). Many sampling-based methods have been proposed for estimating these…

Machine Learning · Computer Science 2020-10-23 Andy Shih , Stefano Ermon