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We present a new, but simple, randomised order-preserving encryption (OPE) scheme based on the general approximate common divisor problem (GACDP). This appears to be the first OPE scheme to be based on a computational hardness primitive,…

Cryptography and Security · Computer Science 2017-06-26 James Dyer , Martin Dyer , Jie Xu

We study ensembles of codes on graphs (generalized low-density parity-check, or LDPC codes) constructed from random graphs and fixed local constrained codes, and their extension to codes on hypergraphs. It is known that the average minimum…

Information Theory · Computer Science 2011-02-22 Alexander Barg , Arya Mazumdar

Many data analysis applications deal with large matrices and involve approximating the matrix using a small number of ``components.'' Typically, these components are linear combinations of the rows and columns of the matrix, and are thus…

Data Structures and Algorithms · Computer Science 2007-08-29 Petros Drineas , Michael W. Mahoney , S. Muthukrishnan

We design improved approximation algorithms for NP-hard graph problems by incorporating predictions (e.g., learned from past data). Our prediction model builds upon and extends the $\varepsilon$-prediction framework by Cohen-Addad, d'Orsi,…

Machine Learning · Computer Science 2025-06-02 Anders Aamand , Justin Y. Chen , Siddharth Gollapudi , Sandeep Silwal , Hao Wu

A $k$-query locally decodable code (LDC) $C$ allows one to encode any $n$-symbol message $x$ as a codeword $C(x)$ of $N$ symbols such that each symbol of $x$ can be recovered by looking at $k$ symbols of $C(x)$, even if a constant fraction…

Information Theory · Computer Science 2021-07-22 Lin Zhu , Wen Ming Li , Liang Feng Zhang

This paper presents a low-complexity near-maximum-likelihood-detection (near-MLD) algorithm called one-bit-sphere-decoding for an uplink massive multiple-input multiple-output (MIMO) system with one-bit analog-to-digital converters (ADCs).…

Information Theory · Computer Science 2017-12-20 Yo-Seb Jeon , Namyoon Lee , Song-Nam Hong , Robert W. Heath

Folded Reed-Solomon codes are an explicit family of codes that achieve the optimal trade-off between rate and error-correction capability: specifically, for any $\eps > 0$, the author and Rudra (2006,08) presented an $n^{O(1/\eps)}$ time…

Information Theory · Computer Science 2016-11-17 Venkatesan Guruswami

We present a general class of unbiased improved estimators for physical observables in lattice gauge theory computations which significantly reduces statistical errors at modest computational cost. The error reduction techniques, referred…

High Energy Physics - Lattice · Physics 2013-11-13 Thomas Blum , Taku Izubuchi , Eigo Shintani

In this paper, we present a generalization of Hayden's theorem [7, Theorem 4.2] for $G$-codes over finite Frobenius rings. A lattice theoretical form of this generalization is also given. Moreover, Astumi's MacWilliams identity [1, Theorem…

Combinatorics · Mathematics 2023-09-11 Himadri Shekhar Chakraborty , Tsuyoshi Miezaki

Consider a distributed coding for computing problem with constant decoding locality, i.e., with a vanishing error probability, any single sample of the function can be approximately recovered by probing only constant number of compressed…

Information Theory · Computer Science 2024-03-01 Deheng Yuan , Tao Guo , Zhongyi Huang , Shi Jin

In this work it is shown that locally repairable codes (LRCs) can be list-decoded efficiently beyond the Johnson radius for a large range of parameters by utilizing the local error-correction capabilities. The corresponding decoding radius…

Information Theory · Computer Science 2020-09-16 Lukas Holzbaur , Sven Puchinger , Antonia Wachter-Zeh

The sum-rank metric generalizes the Hamming and rank metric by partitioning vectors into blocks and defining the total weight as the sum of the rank weights of these blocks, based on their matrix representation. In this work, we explore…

Information Theory · Computer Science 2024-10-22 Thomas Jerkovits , Hannes Bartz , Antonia Wachter-Zeh

The recent development of deep learning methods provides a new approach to optimize the belief propagation (BP) decoding of linear codes. However, the limitation of existing works is that the scale of neural networks increases rapidly with…

Information Theory · Computer Science 2021-02-11 Jincheng Dai , Kailin Tan , Zhongwei Si , Kai Niu , Mingzhe Chen , H. Vincent Poor , Shuguang Cui

We resolve a long-standing open question, about the existence of a constant-factor approximation algorithm for the average-case \textsc{Decision Tree} problem with uniform probability distribution over the hypotheses. We answer the question…

Data Structures and Algorithms · Computer Science 2026-04-29 Michał Szyfelbein

Lattice rules are among the most prominently studied quasi-Monte Carlo methods to approximate multivariate integrals. A rank-1 lattice rule to approximate an $s$-dimensional integral is fully specified by its generating vector $\mathbf{z}…

Numerical Analysis · Mathematics 2020-01-10 Adrian Ebert , Peter Kritzer , Dirk Nuyens , Onyekachi Osisiogu

Given a weighted graph $G$ with $n$ vertices and $m$ edges, and a positive integer $p$, the Hamiltonian $p$-median problem consists in finding $p$ cycles of minimum total weight such that each vertex of $G$ is in exactly one cycle. We…

Data Structures and Algorithms · Computer Science 2022-04-28 Dilson Lucas Pereira , Michel Wan Der Maas Soares

Large-scale distributed learning aims at minimizing a loss function $L$ that depends on a training dataset with respect to a $d$-length parameter vector. The distributed cluster typically consists of a parameter server (PS) and multiple…

Information Theory · Computer Science 2026-03-25 Sifat Munim , Aditya Ramamoorthy

It was recently shown that the problem of decoding messages transmitted through a noisy channel can be formulated as a belief updating task over a probabilistic network [McEliece]. Moreover, it was observed that iterative application of the…

Artificial Intelligence · Computer Science 2013-02-01 Irina Rish , Kalev Kask , Rina Dechter

In this letter, we develop an efficient linear programming (LP) decoding algorithm for low-density parity-check (LDPC) codes. We first relax the maximum likelihood (ML) decoding problem to a LP problem by using check-node decomposition.…

Information Theory · Computer Science 2019-01-24 Jing Bai , Yongchao Wang , Francis C. M. Lau

The generalized alternating direction method of multipliers (ADMM) of Xiao et al. [{\tt Math. Prog. Comput., 2018}] aims at the two-block linearly constrained composite convex programming problem, in which each block is in the form of…

Optimization and Control · Mathematics 2022-04-05 Hongwu Li , Haibin Zhang , Yunhai Xiao