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We provide a unified method for constructing explicit distributions which are difficult for restricted models of computation to generate. Our constructions are based on a new notion of robust extractors, which are extractors that remain…

Computational Complexity · Computer Science 2026-05-11 Farzan Byramji , Daniel M. Kane , Jackson Morris , Anthony Ostuni

Compressed Counting (CC), based on maximally skewed stable random projections, was recently proposed for estimating the p-th frequency moments of data streams. The case p->1 is extremely useful for estimating Shannon entropy of data…

Data Structures and Algorithms · Computer Science 2009-10-09 Ping Li

Shannon entropy is the shortest average codeword length a lossless compressor can achieve by encoding i.i.d. symbols. However, there are cases in which the objective is to minimize the \textit{exponential} average codeword length, i.e. when…

Information Theory · Computer Science 2024-06-10 Andrea Somazzi , Paolo Ferragina , Diego Garlaschelli

Pulsars exhibit signals with precise inter-arrival times that are on the order of milliseconds to seconds, depending on the individual pulsar. There are subtle variations in the timing of pulsar signals. We show that these variations can…

Cryptography and Security · Computer Science 2025-04-24 Hayder Tirmazi

Randomized (dithered) quantization is a method capable of achieving white reconstruction error independent of the source. Dithered quantizers have traditionally been considered within their natural setting of uniform quantization. In this…

Information Theory · Computer Science 2017-04-26 Emrah Akyol , Kenneth Rose

Several conjectures concern the lower bound for the differential entropy $H(X_t)$ of an $n$-dimensional random vector $X_t$ introduced by Costa. Cheng and Geng conjectured that $H(X_t)$ is completely monotone, that is, $C_1(m,n):…

Information Theory · Computer Science 2020-07-21 Laigang Guo , Chun-Ming Yuan , Xiao-Shan Gao

A random variable $X$ is an $(n,k)$-zero-fixing source if for some subset $V\subseteq[n]$, $X$ is the uniform distribution on the strings $\{0,1\}^n$ that are zero on every coordinate outside of $V$. An $\epsilon$-extractor for…

Computational Complexity · Computer Science 2019-12-18 Pavel Pudlák , Vojtech Rödl

Poulin, Tillich, and Ollivier discovered an important separation between the classical and quantum theories of convolutional coding, by proving that a quantum convolutional encoder cannot be both non-catastrophic and recursive.…

Quantum Physics · Physics 2013-12-09 Monireh Houshmand , Mark M. Wilde

We describe a methodology and standard of proof for experimental claims of quantum random number generation (QRNG), analogous to well-established methods from precision measurement. For appropriately constructed physical implementations,…

Quantum Physics · Physics 2015-01-14 Morgan W. Mitchell , Carlos Abellan , Waldimar Amaya

We consider the problem of identifying the causal direction between two discrete random variables using observational data. Unlike previous work, we keep the most general functional model but make an assumption on the unobserved exogenous…

Artificial Intelligence · Computer Science 2016-11-16 Murat Kocaoglu , Alexandros G. Dimakis , Sriram Vishwanath , Babak Hassibi

A general multi-terminal source code and a general multi-terminal channel code are presented. Constrained-random-number generators with sparse matrices, which are building blocks for the code construction, are used in the construction of…

Information Theory · Computer Science 2018-01-11 Jun Muramatsu , Shigeki Miyake

How to generate provably true randomness with minimal assumptions? This question is important not only for the efficiency and the security of information processing, but also for understanding how extremely unpredictable events are possible…

Quantum Physics · Physics 2015-05-18 Kai-Min Chung , Yaoyun Shi , Xiaodi Wu

Brakerski et. al [BCM+18] introduced the model of cryptographic testing of a single untrusted quantum device and gave a protocol for certifiable randomness generation. We use the leakage resilience properties of the Learning With Errors…

Quantum Physics · Physics 2022-04-26 Urmila Mahadev , Umesh Vazirani , Thomas Vidick

This article studies the fundamental problem of using i.i.d. coin tosses from an entropy source to efficiently generate random variables $X_i \sim P_i$ $(i \ge 1)$, where $(P_1, P_2, \dots)$ is a random sequence of rational discrete…

Data Structures and Algorithms · Computer Science 2026-05-08 Thomas L. Draper , Feras A. Saad

In this paper, we propose a source coding scheme that represents data from unknown distributions through frequency and support information. Existing encoding schemes often compress data by sacrificing computational efficiency or by assuming…

Information Theory · Computer Science 2024-10-28 Leah Woldemariam , Hang Liu , Anna Scaglione

We consider the problem of extracting entropy by sparse transformations, namely functions with a small number of overall input-output dependencies. In contrast to previous works, we seek extractors for essentially all the entropy without…

Computational Complexity · Computer Science 2012-07-27 Andrej Bogdanov , Siyao Guo

We propose a new model of a weakly random source that admits randomness extraction. Our model of additive sources includes such natural sources as uniform distributions on arithmetic progressions (APs), generalized arithmetic progressions…

Computational Complexity · Computer Science 2014-10-28 Abhishek Bhowmick , Ariel Gabizon , Thái Hoàng Lê , David Zuckerman

It is shown that an i.i.d. binary source sequence $X_1, \ldots, X_n$ can be losslessly compressed at any rate above entropy such that the individual decoding of any $X_i$ reveals \emph{no} information about the other bits $\{X_j : j \neq…

Information Theory · Computer Science 2025-11-19 Venkat Chandar , Aslan Tchamkerten , Shashank Vatedka

The Contrastive Divergence (CD) algorithm has achieved notable success in training energy-based models including Restricted Boltzmann Machines and played a key role in the emergence of deep learning. The idea of this algorithm is to…

Machine Learning · Statistics 2018-03-01 Bai Jiang , Tung-Yu Wu , Yifan Jin , Wing H. Wong

As a fundamental phenomenon in nature, randomness has a wide range of applications in the fields of science and engineering. Among different types of random number generators (RNG), quantum random number generator (QRNG) is a kind of…

Quantum Physics · Physics 2019-04-19 Bingjie Xu , Ziyang Chen , Zhengyu Li , Jie Yang , Qi Su , Wei Huang , Yichen Zhang , Hong Guo