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Related papers: Lightweight Lempel-Ziv Parsing

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A distributed network is modeled by a graph having $n$ nodes (processors) and diameter $D$. We study the time complexity of approximating {\em weighted} (undirected) shortest paths on distributed networks with a $O(\log n)$ {\em bandwidth…

Data Structures and Algorithms · Computer Science 2014-05-23 Danupon Nanongkai

Re-Pair is an effective grammar-based compression scheme achieving strong compression rates in practice. Let $n$, $\sigma$, and $d$ be the text length, alphabet size, and dictionary size of the final grammar, respectively. In their original…

Data Structures and Algorithms · Computer Science 2016-11-07 Philip Bille , Inge Li Gørtz , Nicola Prezza

We give algorithms that, given a straight-line program (SLP) with $g$ rules that generates (only) a text $T [1..n]$, builds within $O(g)$ space the Lempel-Ziv (LZ) parse of $T$ (of $z$ phrases) in time $O(n\log^2 n)$ or in time…

Data Structures and Algorithms · Computer Science 2023-10-11 Travis Gagie , Adrián Goga , Artur Jeż , Gonzalo Navarro

Today there are many universal compression algorithms, but in most cases is for specific data better using specific algorithm - JPEG for images, MPEG for movies, etc. For textual documents there are special methods based on PPM algorithm or…

Information Theory · Computer Science 2008-12-18 Jan Platos , Jiri Dvorsky

We raise the question of approximating the compressibility of a string with respect to a fixed compression scheme, in sublinear time. We study this question in detail for two popular lossless compression schemes: run-length encoding (RLE)…

Data Structures and Algorithms · Computer Science 2007-06-11 Sofya Raskhodnikova , Dana Ron , Ronitt Rubinfeld , Adam Smith

Deep learning models have become state of the art for natural language processing (NLP) tasks, however deploying these models in production system poses significant memory constraints. Existing compression methods are either lossy or…

Machine Learning · Computer Science 2018-11-05 Anish Acharya , Rahul Goel , Angeliki Metallinou , Inderjit Dhillon

Advances in DNA sequencing mean databases of thousands of human genomes will soon be commonplace. In this paper we introduce a simple technique for reducing the size of conventional indexes on such highly repetitive texts. Given upper…

Data Structures and Algorithms · Computer Science 2015-06-16 H. Ferrada , T. Gagie , T. Hirvola , S. J. Puglisi

LZ77-based compression schemes compress the input text by replacing factors in the text with an encoded reference to a previous occurrence formed by the couple (length, offset). For a given factor, the smallest is the offset, the smallest…

Data Structures and Algorithms · Computer Science 2012-11-22 Maxime Crochemore , Alessio Langiu , Filippo Mignosi

A new deterministic algorithm for finding square divisors, and finding $r$-power divisors in general, is presented. This algorithm is based on Lehman's method for integer factorization and is straightforward to implement. While the…

Number Theory · Mathematics 2022-10-03 Jonathon Hales , Ghaith Hiary

Binary quantization approaches, which replace weight matrices with binary matrices and substitute costly multiplications with cheaper additions, offer a computationally efficient approach to address the increasing computational and storage…

Machine Learning · Computer Science 2026-03-03 Vladimír Boža , Vladimír Macko

In a \emph{weighted sequence}, for every position of the sequence and every letter of the alphabet a probability of occurrence of this letter at this position is specified. Weighted sequences are commonly used to represent imprecise or…

Data Structures and Algorithms · Computer Science 2017-08-28 Carl Barton , Tomasz Kociumaka , Chang Liu , Solon P. Pissis , Jakub Radoszewski

Computation on compressed strings is one of the key approaches to processing massive data sets. We consider local subsequence recognition problems on strings compressed by straight-line programs (SLP), which is closely related to…

Data Structures and Algorithms · Computer Science 2011-11-10 Alexander Tiskin

In this paper we present a simple linear-time algorithm constructing a context-free grammar of size O(g log(N/g)) for the input string, where N is the size of the input string and g the size of the optimal grammar generating this string.…

Data Structures and Algorithms · Computer Science 2013-11-08 Artur Jeż

The compressed indexing problem is to preprocess a string $S$ of length $n$ into a compressed representation that supports pattern matching queries. That is, given a string $P$ of length $m$ report all occurrences of $P$ in $S$. We present…

Data Structures and Algorithms · Computer Science 2018-04-12 Anders Roy Christiansen , Mikko Berggren Ettienne

There has been significant interest and progress recently in algorithms that solve regression problems involving tall and thin matrices in input sparsity time. These algorithms find shorter equivalent of a n*d matrix where n >> d, which…

Data Structures and Algorithms · Computer Science 2013-04-05 Mu Li , Gary L. Miller , Richard Peng

Deep neural networks (DNNs) are often used for text classification tasks as they usually achieve high levels of accuracy. However, DNNs can be computationally intensive with billions of parameters and large amounts of labeled data, which…

Computation and Language · Computer Science 2022-12-20 Zhiying Jiang , Matthew Y. R. Yang , Mikhail Tsirlin , Raphael Tang , Jimmy Lin

We present new algorithms to detect and correct errors in the lower-upper factorization of a matrix, or the triangular linear system solution, over an arbitrary field. Our main algorithms do not require any additional information or…

Symbolic Computation · Computer Science 2019-01-31 Jean-Guillaume Dumas , Joris Van Der Hoeven , Clément Pernet , Daniel Roche

Grammar compression is, next to Lempel-Ziv (LZ77) and run-length Burrows-Wheeler transform (RLBWT), one of the most flexible approaches to representing and processing highly compressible strings. The main idea is to represent a text as a…

Data Structures and Algorithms · Computer Science 2022-01-06 Dominik Kempa , Ben Langmead

We describe ways to define and calculate $L_1$-norm signal subspaces which are less sensitive to outlying data than $L_2$-calculated subspaces. We start with the computation of the $L_1$ maximum-projection principal component of a data…

Data Structures and Algorithms · Computer Science 2015-06-19 Panos P. Markopoulos , George N. Karystinos , Dimitris A. Pados

Let $n = \mathrm{p}\!\cdot\!\mathrm{q}$ (p < q) and $\Delta = \lvert p-q \rvert$, where p,q are odd integers, then, it is hypothesized that factorizing this composite n will take O(1) time once the steady state value is reached for any…

Number Theory · Mathematics 2021-09-21 Vishal Mudgal
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