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We consider the variable-to-fixed length lossy source coding (VFSC) problem. The optimal compression rate of the average length of variable-to-fixed source coding, allowing a non-vanishing probability of excess-distortion $\varepsilon$, is…

Information Theory · Computer Science 2018-03-20 Lan V. Truong , Vincent Y. F. Tan

The pseudo-random number generators (PRNGs), sampling algorithms, and algorithms for generating random integers in some common statistical packages and programming languages are unnecessarily inaccurate, by an amount that may matter for…

Computation · Statistics 2018-10-29 Philip B. Stark , Kellie Ottoboni

The problem of joint universal source coding and identification is considered in the setting of fixed-rate lossy coding of continuous-alphabet memoryless sources. For a wide class of bounded distortion measures, it is shown that any…

Information Theory · Computer Science 2007-07-13 Maxim Raginsky

Random numbers sequences (RNSs) play a vital role in various scientific and engineering applications. They are critical to the integrity of classical and quantum cryptography, the accuracy of mathematical modeling and Monte Carlo…

Quantum random number generators can provide genuine randomness by appealing to the fundamental principles of quantum mechanics. In general, a physical generator contains two parts---a randomness source and its readout. The source is…

Quantum Physics · Physics 2016-03-01 Zhu Cao , Hongyi Zhou , Xiao Yuan , Xiongfeng Ma

The future of high-performance computing is aligning itself towards the efficient use of highly parallel computing environments. One application where the use of massive parallelism comes instinctively is Monte Carlo simulations, where a…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-01-11 S. Hissoiny , P. Després , B. Ozell

We introduce an improved version of Random Search (RS), used here for hyperparameter optimization of machine learning algorithms. Unlike the standard RS, which generates for each trial new values for all hyperparameters, we generate new…

Machine Learning · Computer Science 2020-04-06 Adrian-Catalin Florea , Razvan Andonie

In this paper we consider lossless source coding for a class of sources specified by the total variational distance ball centred at a fixed nominal probability distribution. The objective is to find a minimax average length source code,…

Information Theory · Computer Science 2013-01-25 Themistoklis Charalambous , Charalambos D. Charalambous , Sergey Loyka

A quantum random number generator (QRNG) based on gated single photon detection of an InGaAs photodiode at GHz frequency is demonstrated. Owing to the extremely long coherence time of each photon, each photons' wavefuntion extends over many…

Quantum Physics · Physics 2008-07-28 J. F. Dynes , Z. L. Yuan , A. W. Sharpe , A. J. Shields

Recurrent neural networks (RNNs) are known to be universal approximators of dynamic systems under fairly mild and general assumptions. However, RNNs usually suffer from the issues of vanishing and exploding gradients in standard RNN…

Signal Processing · Electrical Eng. & Systems 2024-10-28 Shashank Jere , Lizhong Zheng , Karim Said , Lingjia Liu

Quantum random number generator (QRNG) is one of the most widely applied branches in quantum cryptography. Among all QRNG schemes, semi-device-independent (semi-DI) QRNG is quite promising, achieving high randomness generation rate with few…

Quantum Physics · Physics 2023-09-26 Hongyi Zhou

Random number generation is fundamental for many modern applications including cryptography, simulations and machine learning. Traditional pseudo-random numbers may offer statistical unpredictability, but are ultimately deterministic. On…

Quantum Physics · Physics 2025-12-11 Andrzej Gnatowski , Jarosław Rudy , Teodor Niżyński , Krzysztof Święcicki

We present an efficient method to extract the amount of true randomness that can be obtained by a Quantum Random Number Generator (QRNG). By repeating the measurements of a quantum system and by swapping between two mutually unbiased bases,…

Quantum Physics · Physics 2014-12-23 G. Vallone , D. Marangon , M. Tomasin , P. Villoresi

The effectiveness of training neural networks directly impacts computational costs, resource allocation, and model development timelines in machine learning applications. An optimizer's ability to train the model adequately (in terms of…

Machine Learning · Computer Science 2024-08-06 Andriy Miranskyy , Adam Sorrenti , Viral Thakar

This work concerns the analysis and design of distributed first-order optimization algorithms over time-varying graphs. The goal of such algorithms is to optimize a global function that is the average of local functions using only local…

Optimization and Control · Mathematics 2020-02-17 Akhil Sundararajan , Bryan Van Scoy , Laurent Lessard

Quantum random number generators (QRNGs) harness quantum mechanical unpredictability to produce true randomness, which is crucial for cryptography and secure communications. Among various QRNGs, source-independent QRNGs (SI-QRNGs) relax the…

Quantum Physics · Physics 2024-11-25 Hongyi Zhou

Quantum random number generator harnesses the power of quantum mechanics to generate true random numbers, making it valuable for various scientific applications. However, real-world devices often suffer from imperfections that can undermine…

Quantum Physics · Physics 2023-12-07 Xing Lin , Rong Wang

This paper targets to search so-called \emph{good} generators by doing a brief survey over the generators developed in the history of pseudo-random number generators (PRNGs), verify their claims and rank them based on strong empirical tests…

Cryptography and Security · Computer Science 2025-08-19 Kamalika Bhattacharjee , Sukanta Das

This paper studies the fixed budget formulation of the Ranking and Selection (R&S) problem with independent normal samples, where the goal is to investigate different algorithms' convergence rate in terms of their resulting probability of…

Optimization and Control · Mathematics 2018-11-30 Di Wu , Enlu Zhou

Quantum random number generators (QRNGs) output genuine random numbers based upon the uncertainty principle. A QRNG contains two parts in general --- a randomness source and a readout detector. How to remove detector imperfections has been…

Quantum Physics · Physics 2016-01-14 Zhu Cao , Hongyi Zhou , Xiongfeng Ma
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