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Large Language Models are growing in size, and we expect them to continue to do so, as larger models train quicker. However, this increase in size will severely impact inference costs. Therefore model compression is important, to retain the…

Machine Learning · Computer Science 2024-04-10 Georgy Tyukin

We consider the problem of decompressing the Lempel--Ziv 77 representation of a string $S$ of length $n$ using a working space as close as possible to the size $z$ of the input. The folklore solution for the problem runs in $O(n)$ time but…

Data Structures and Algorithms · Computer Science 2019-11-05 Philip Bille , Mikko Berggren Ettienne , Travis Gagie , Inge Li Gørtz , Nicola Prezza

The Recurrent Neural Networks and their variants have shown promising performances in sequence modeling tasks such as Natural Language Processing. These models, however, turn out to be impractical and difficult to train when exposed to very…

Computer Vision and Pattern Recognition · Computer Science 2017-07-07 Yinchong Yang , Denis Krompass , Volker Tresp

Modern data compression methods are slowly reaching their limits after 80 years of research, millions of papers, and wide range of applications. Yet, the extravagant 6G communication speed requirement raises a major open question for…

Information Theory · Computer Science 2025-05-01 Ziguang Li , Chao Huang , Xuliang Wang , Haibo Hu , Cole Wyeth , Dongbo Bu , Quan Yu , Wen Gao , Xingwu Liu , Ming Li

Label prediction in neural networks (NNs) has O(n) complexity proportional to the number of classes. This holds true for classification using fully connected layers and cosine similarity with some set of class prototypes. In this paper we…

Machine Learning · Computer Science 2026-04-07 Nikita Gabdullin , Ilya Androsov

We observe that any $T(n)$ time algorithm (quantum or classical) for several central linear algebraic problems, such as computing $\det(A)$, $tr(A^3)$, or $tr(A^{-1})$ for an $n \times n$ integer matrix $A$, yields a $O(T(n)) + \tilde…

Data Structures and Algorithms · Computer Science 2025-09-25 Kyle Doney , Cameron Musco

A Longest Common Extension (LCE) query on a text $T$ of length $N$ asks for the length of the longest common prefix of suffixes starting at given two positions. We show that the signature encoding $\mathcal{G}$ of size $w = O(\min(z \log N…

Data Structures and Algorithms · Computer Science 2016-06-28 Takaaki Nishimoto , Tomohiro I , Shunsuke Inenaga , Hideo Bannai , Masayuki Takeda

As state of the art neural networks (NNs) continue to grow in size, their resource-efficient implementation becomes ever more important. In this paper, we introduce a compression scheme that reduces the number of computations required for…

Machine Learning · Computer Science 2025-04-25 Hans Rosenberger , Rodrigo Fischer , Johanna S. Fröhlich , Ali Bereyhi , Ralf R. Müller

In the field of biological research, it is essential to comprehend the characteristics and functions of molecular sequences. The classification of molecular sequences has seen widespread use of neural network-based techniques. Despite their…

Machine Learning · Computer Science 2024-02-14 Sarwan Ali , Tamkanat E Ali , Prakash Chourasia , Murray Patterson

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

It was recently proved that any Straight-Line Program (SLP) generating a given string can be transformed in linear time into an equivalent balanced SLP of the same asymptotic size. We generalize this proof to a general class of grammars we…

Data Structures and Algorithms · Computer Science 2024-04-11 Gonzalo Navarro , Francisco Olivares , Cristian Urbina

Directional interpolation is a fast and efficient compression technique for high-frequency Helmholtz boundary integral equations, but it requires a very large amount of storage in its original form. Algebraic recompression can significantly…

Numerical Analysis · Mathematics 2023-10-23 Steffen Börm , Janne Henningsen

In memory-constrained algorithms we have read-only access to the input, and the number of additional variables is limited. In this paper we introduce the compressed stack technique, a method that allows to transform algorithms whose space…

Computational Geometry · Computer Science 2014-06-26 Luis Barba , Matias Korman , Stefan Langerman , Kunikiko Sadakane , Rodrigo Silveira

In numerical linear algebra, considerable effort has been devoted to obtaining faster algorithms for linear systems whose underlying matrices exhibit structural properties. A prominent success story is the method of generalized nested…

Data Structures and Algorithms · Computer Science 2023-10-26 Sally Dong , Gramoz Goranci , Lawrence Li , Sushant Sachdeva , Guanghao Ye

We give the first computationally tractable and almost optimal solution to the problem of one-bit compressed sensing, showing how to accurately recover an s-sparse vector x in R^n from the signs of O(s log^2(n/s)) random linear measurements…

Information Theory · Computer Science 2015-03-19 Yaniv Plan , Roman Vershynin

The inherent diversity of computation types within the deep neural network (DNN) models often requires a variety of specialized units in hardware processors, which limits computational efficiency, increasing both inference latency and power…

Machine Learning · Computer Science 2024-08-21 Ruiqi Sun , Siwei Ye , Jie Zhao , Xin He , Jianzhe Lin , Yiran Li , An Zou

Grammar based compression, where one replaces a long string by a small context-free grammar that generates the string, is a simple and powerful paradigm that captures many popular compression schemes. In this paper, we present a novel…

Data Structures and Algorithms · Computer Science 2013-10-30 Philip Bille , Gad M. Landau , Rajeev Raman , Kunihiko Sadakane , Srinivasa Rao Satti , Oren Weimann

Let a text $T[1..n]$ be the only string generated by a context-free grammar with $g$ (terminal and nonterminal) symbols, and of size $G$ (measured as the sum of the lengths of the right-hand sides of the rules). Such a grammar, called a…

Data Structures and Algorithms · Computer Science 2020-04-03 Francisco Claude , Gonzalo Navarro , Alejandro Pacheco

In this paper, a fully compressed pattern matching problem is studied. The compression is represented by straight-line programs (SLPs), i.e. a context-free grammars generating exactly one string; the term fully means that both the pattern…

Data Structures and Algorithms · Computer Science 2013-06-26 Artur Jeż

The polynomial multiplication problem has attracted considerable attention since the early days of computer algebra, and several algorithms have been designed to achieve the best possible time complexity. More recently, efforts have been…

Symbolic Computation · Computer Science 2019-02-11 Pascal Giorgi , Bruno Grenet , Daniel Roche