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Various grammar compression algorithms have been proposed in the last decade. A grammar compression is a restricted CFG deriving the string deterministically. An efficient grammar compression develops a smaller CFG by finding duplicated…

Data Structures and Algorithms · Computer Science 2016-09-01 Shouhei Fukunaga , Yoshimasa Takabatake , I Tomohiro , Hiroshi Sakamoto

We present a compressed representation of tries based on top tree compression [ICALP 2013] that works on a standard, comparison-based, pointer machine model of computation and supports efficient prefix search queries. Namely, we show how to…

Data Structures and Algorithms · Computer Science 2019-09-23 Philip Bille , Inge Li Gørtz , Paweł Gawrychowski , Gad M. Landau , Oren Weimann

Dense and sparse tensors allow the representation of most bulk data structures in computational science applications. We show that sparse tensor algebra can also be used to express many of the transformations on these datasets, especially…

Mathematical Software · Computer Science 2015-12-02 Edgar Solomonik , Torsten Hoefler

We propose to store several integers modulo a small prime into a single machine word. Modular addition is performed by addition and possibly subtraction of a word containing several times the modulo. Modular Multiplication is not directly…

Symbolic Computation · Computer Science 2008-12-18 Jean-Guillaume Dumas , Laurent Fousse , Bruno Salvy

It is shown that every tree of size $n$ over a fixed set of $\sigma$ different ranked symbols can be decomposed (in linear time as well as in logspace) into $O\big(\frac{n}{\log_\sigma n}\big) = O\big(\frac{n \log \sigma}{\log n}\big)$ many…

Data Structures and Algorithms · Computer Science 2015-09-22 Moses Ganardi , Danny Hucke , Artur Jez , Markus Lohrey , Eric Noeth

Neural networks using numerous text data have been successfully applied to a variety of tasks. While massive text data is usually compressed using techniques such as grammar compression, almost all of the previous machine learning methods…

Machine Learning · Statistics 2020-03-02 Yoichi Sasaki , Kosuke Akimoto , Takanori Maehara

The LZ-End parsing [Kreft & Navarro, 2011] of an input string yields compression competitive with the popular Lempel-Ziv 77 scheme, but also allows for efficient random access. Kempa and Kosolobov showed that the parsing can be computed in…

Data Structures and Algorithms · Computer Science 2024-09-18 Patrick Dinklage

There have been several algorithms designed to optimise matrix multiplication. From schoolbook method with complexity $O(n^3)$ to advanced tensor-based tools with time complexity $O(n^{2.3728639})$ (lowest possible bound achieved), a lot of…

Data Structures and Algorithms · Computer Science 2019-01-30 Shrohan Mohapatra

A randomized algorithm for computing a compressed representation of a given rank-structured matrix $A \in \mathbb{R}^{N\times N}$ is presented. The algorithm interacts with $A$ only through its action on vectors. Specifically, it draws two…

Numerical Analysis · Mathematics 2024-06-25 James Levitt , Per-Gunnar Martinsson

The matrix chain problem consists in finding the parenthesization of a matrix product $M := A_1 A_2 \cdots A_n$ that minimizes the number of scalar operations. In practical applications, however, one frequently encounters more complicated…

Data Structures and Algorithms · Computer Science 2016-11-18 Henrik Barthels , Paolo Bientinesi

Linear programming is a powerful method in combinatorial optimization with many applications in theory and practice. For solving a linear program quickly it is desirable to have a formulation of small size for the given problem. A useful…

Data Structures and Algorithms · Computer Science 2019-02-28 Hans Raj Tiwary , Victor Verdugo , Andreas Wiese

Compressed indexing is a powerful technique that enables efficient querying over data stored in compressed form, significantly reducing memory usage and often accelerating computation. While extensive progress has been made for…

Data Structures and Algorithms · Computer Science 2025-10-23 Rajat De , Dominik Kempa

Boundary integral equations lead to dense system matrices when discretized, yet they are data-sparse. Using the $\mathcal{H}$-matrix format, this sparsity is exploited to achieve $\mathcal{O}(N\log N)$ complexity for storage and…

Numerical Analysis · Mathematics 2025-05-22 Kobe Bruyninckx , Daan Huybrechs , Karl Meerbergen

We consider the problem of finding the smallest or largest entry of a tensor of order N that is specified via its rank decomposition. Stated in a different way, we are given N sets of R-dimensional vectors and we wish to select one vector…

Signal Processing · Electrical Eng. & Systems 2023-12-25 Nicholas D. Sidiropoulos , Paris Karakasis , Aritra Konar

In 1981 Hong and Kung proved a lower bound on the amount of communication needed to perform dense, matrix-multiplication using the conventional $O(n^3)$ algorithm, where the input matrices were too large to fit in the small, fast memory. In…

Computational Complexity · Computer Science 2011-09-20 Grey Ballard , James Demmel , Olga Holtz , Oded Schwartz

Mauer et al. [A Lempel-Ziv-style Compression Method for Repetitive Texts, PSC 2017] proposed a hybrid text compression method called LZ-LFS which has both features of Lempel-Ziv 77 factorization and longest first substitution. They showed…

Data Structures and Algorithms · Computer Science 2018-06-14 Akihiro Nishi , Yuto Nakashima , Shunsuke Inenaga , Hideo Bannai , Masayuki Takeda

Given a string $T$ of length $N$, the goal of grammar compression is to construct a small context-free grammar generating only $T$. Among existing grammar compression methods, RePair (recursive paring) [Larsson and Moffat, 1999] is notable…

Data Structures and Algorithms · Computer Science 2018-11-06 Kensuke Sakai , Tatsuya Ohno , Keisuke Goto , Yoshimasa Takabatake , Tomohiro I , Hiroshi Sakamoto

To store and search genomic databases efficiently, researchers have recently started building compressed self-indexes based on grammars. In this paper we show how, given a straight-line program with $r$ rules for a string (S [1..n]) whose…

Data Structures and Algorithms · Computer Science 2012-09-28 Travis Gagie , Paweł Gawrychowski , Juha Kärkkäinen , Yakov Nekrich , Simon J. Puglisi

A $\textit{compression scheme}$ $A$ for a class $\mathbb{G}$ of graphs consists of an encoding algorithm $\textit{Encode}_A$ that computes a binary string $\textit{Code}_A(G)$ for any given graph $G$ in $\mathbb{G}$ and a decoding algorithm…

Data Structures and Algorithms · Computer Science 2014-04-24 Hsueh-I Lu

Sublinear time quantum algorithms have been established for many fundamental problems on strings. This work demonstrates that new, faster quantum algorithms can be designed when the string is highly compressible. We focus on two popular and…

Data Structures and Algorithms · Computer Science 2023-02-15 Daniel Gibney , Sharma V. Thankachan