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Gaussian random number generators attract a widespread interest due to their applications in several fields. Important requirements include easy implementation, tail accuracy, and, finally, a flat spectrum. In this work, we study the…

Information Theory · Computer Science 2024-04-04 Francisco-Javier Soto , Ana I. Gómez , Domingo Gómez-Pérez

Recently, a secrecy measure based on list-reconstruction has been proposed [2], in which a wiretapper is allowed to produce a list of $2^{mR_{L}}$ reconstruction sequences and the secrecy is measured by the minimum distortion over the…

Information Theory · Computer Science 2017-07-25 Lei Yu , Houqiang Li , Weiping Li

We describe a class of cellular automata (CAs) that are end-to-end differentiable. DCAs interpolate the behavior of ordinary CAs through rules that act on distributions of states. The gradient of a DCA with respect to its parameters can be…

Discrete Mathematics · Computer Science 2017-09-01 Carlos Martin

Monte Carlo simulations are one of the major tools in statistical physics, complex system science, and other fields, and an increasing number of these simulations is run on distributed systems like clusters or grids. This raises the issue…

Other Condensed Matter · Physics 2007-07-03 Heiko Bauke , Stephan Mertens

Under the emerging network coding paradigm, intermediate nodes in the network are allowed not only to store and forward packets but also to process and mix different data flows. We propose a low-complexity cryptographic scheme that exploits…

Cryptography and Security · Computer Science 2016-11-17 Joao P. Vilela , Luisa Lima , Joao Barros

Linear codes have diverse applications in secret sharing schemes, secure two-party computation, association schemes, strongly regular graphs, authentication codes and communication. There are a large number of linear codes with few weights…

Information Theory · Computer Science 2020-05-12 Ahmet Sınak

We study the task of smoothing a circuit, i.e., ensuring that all children of a plus-gate mention the same variables. Circuits serve as the building blocks of state-of-the-art inference algorithms on discrete probabilistic graphical models…

Artificial Intelligence · Computer Science 2019-10-29 Andy Shih , Guy Van den Broeck , Paul Beame , Antoine Amarilli

A new cryptographic approach -- Iterated Random Encryption (IRE) -- is presented here. Although it is very simple, and easy to implement, it provides a very high level of security. According to this approach, a sequence of operations…

Cryptography and Security · Computer Science 2018-10-30 Osvaldo Skliar , Sherry Gapper , Ricardo E. Monge

In this paper, we present a probabilistic analysis of iterative node-based verification-based (NB-VB) recovery algorithms over irregular graphs in the context of compressed sensing. Verification-based algorithms are particularly interesting…

Information Theory · Computer Science 2012-04-24 Yaser Eftekhari , Amir H. Banihashemi , Ioannis Lambadaris

A Riemannian gradient descent algorithm and a truncated variant are presented to solve systems of phaseless equations $|Ax|^2=y$. The algorithms are developed by exploiting the inherent low rank structure of the problem based on the…

Numerical Analysis · Mathematics 2018-09-11 Jian-Feng Cai , Ke Wei

The Reservoir Computing (RC) paradigm utilizes a dynamical system, i.e., a reservoir, and a linear classifier, i.e., a read-out layer, to process data from sequential classification tasks. In this paper the usage of Cellular Automata (CA)…

Emerging Technologies · Computer Science 2017-02-14 Stefano Nichele , Magnus S. Gundersen

Constrained sequence codes have been widely used in modern communication and data storage systems. Sequences encoded with constrained sequence codes satisfy constraints imposed by the physical channel, hence enabling efficient and reliable…

Information Theory · Computer Science 2018-09-07 Congzhe Cao , Duanshun Li , Ivan Fair

Semantic parsing is the problem of deriving machine interpretable meaning representations from natural language utterances. Neural models with encoder-decoder architectures have recently achieved substantial improvements over traditional…

Computation and Language · Computer Science 2019-09-30 Huseyin A. Inan , Gaurav Singh Tomar , Huapu Pan

The analysis of intermittent data is improved. The standard method of recovering the history of a particle cascade is proved in general not to reproduce the structure of the true cascade. The recovering corrections to the standard method…

High Energy Physics - Phenomenology · Physics 2011-09-13 B. Ziaja

Pseudorandom bit generators (PRBG) can be designed to take the advantage of some hard number theoretic problems such as the discrete logarithm problem (DLP). Such type of generators will have good randomness and unpredictability properties…

Cryptography and Security · Computer Science 2020-02-24 O. Reyad , M. E. Karar , K. Hamed

This work investigates the inverse problem of generator recovery in matrix Lie groups from discretized trajectories. Let $G$ be a real matrix Lie group and $\mathfrak{g} = \text{Lie}(G)$ its corresponding Lie algebra. A smooth trajectory…

Machine Learning · Computer Science 2025-04-07 Lifan Hu

Many scientific computing problems can be reduced to Matrix-Matrix Multiplications (MMM), making the General Matrix Multiply (GEMM) kernels in the Basic Linear Algebra Subroutine (BLAS) of interest to the high-performance computing…

Hardware Architecture · Computer Science 2023-05-31 Louis Ledoux , Marc Casas

Regenerating codes provide an efficient way to recover data at failed nodes in distributed storage systems. It has been shown that regenerating codes can be designed to minimize the per-node storage (called MSR) or minimize the…

Information Theory · Computer Science 2014-06-26 Yunghsiang Han , Hung-Ta Pai , Rong Zheng , Pramod K. Varshney

The cellular automaton is a widely known model of both reversible and irreversible computations. The family of reversible second-order cellular automata considered in this work is appropriate both for construction of logic gates and…

Cellular Automata and Lattice Gases · Physics 2024-05-10 Alexander Yu. Vlasov

Mixed linear regression involves the recovery of two (or more) unknown vectors from unlabeled linear measurements; that is, where each sample comes from exactly one of the vectors, but we do not know which one. It is a classic problem, and…

Machine Learning · Statistics 2014-02-10 Xinyang Yi , Constantine Caramanis , Sujay Sanghavi