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We generalize Karp-Rabin string matching to handle multiple patterns in $\mathcal{O}(n \log n + m)$ time and $\mathcal{O}(s)$ space, where $n$ is the length of the text and $m$ is the total length of the $s$ patterns, returning correct…

Data Structures and Algorithms · Computer Science 2015-09-11 Johannes Fischer , Travis Gagie , Paweł Gawrychowski , Tomasz Kociumaka

In this paper, we present near-optimal space bounds for Lp-samplers. Given a stream of updates (additions and subtraction) to the coordinates of an underlying vector x \in R^n, a perfect Lp sampler outputs the i-th coordinate with…

Data Structures and Algorithms · Computer Science 2010-12-23 Hossein Jowhari , Mert Sağlam , Gábor Tardos

It has recently been shown that for compressive sensing, significantly fewer measurements may be required if the sparsity assumption is replaced by the assumption the unknown vector lies near the range of a suitably-chosen generative model.…

Information Theory · Computer Science 2020-03-11 Zhaoqiang Liu , Jonathan Scarlett

We consider compact representations of collections of similar strings that support random access queries. The collection of strings is given by a rooted tree where edges are labeled by an edit operation (inserting, deleting, or replacing a…

Data Structures and Algorithms · Computer Science 2021-02-12 Philip Bille , Inge Li Gørtz

We introduce a novel entropy-related function, \textit{non-repeatability}, designed to capture dynamical behaviors in complex systems. Its normalized form, \textit{mutability}, has been previously applied in statistical physics as a…

Statistical Mechanics · Physics 2025-04-04 Eugenio E. Vogel , Francisco J. Peña , G. Saravia , P. Vargas

We present a simple adaptation of the Lempel Ziv 78' (LZ78) compression scheme ({\em IEEE Transactions on Information Theory, 1978}) that supports efficient random access to the input string. Namely, given query access to the compressed…

Data Structures and Algorithms · Computer Science 2013-01-14 Akashnil Dutta , Reut Levi , Dana Ron , Ronitt Rubinfeld

The goal of compressed sensing is to estimate a vector from an underdetermined system of noisy linear measurements, by making use of prior knowledge on the structure of vectors in the relevant domain. For almost all results in this…

Machine Learning · Statistics 2017-03-10 Ashish Bora , Ajil Jalal , Eric Price , Alexandros G. Dimakis

A regular expression specifies a set of strings formed by single characters combined with concatenation, union, and Kleene star operators. Given a regular expression $R$ and a string $Q$, the regular expression matching problem is to decide…

Data Structures and Algorithms · Computer Science 2023-11-07 Philip Bille , Inge Li Gørtz

Random sequences attain the highest entropy rate. The estimation of entropy rate for an ergodic source can be done using the Lempel Ziv complexity measure yet, the exact entropy rate value is only reached in the infinite limit. We prove…

Chaotic Dynamics · Physics 2013-11-05 E. Estevez-Rams , R. Lora Serrano , B. Aragón Fernández , I. Brito Reyes

We present a new algorithm for computing the Lempel-Ziv Factorization (LZ77) of a given string of length $N$ in linear time, that utilizes only $N\log N + O(1)$ bits of working space, i.e., a single integer array, for constant size integer…

Data Structures and Algorithms · Computer Science 2013-10-08 Keisuke Goto , Hideo Bannai

We consider two theorems from the theory of compressive sensing. Mainly a theorem concerning uniform recovery of random sampling matrices, where the number of samples needed in order to recover an $s$-sparse signal from linear measurements…

Information Theory · Computer Science 2013-06-05 Joel Andersson , Jan-Olov Strömberg

Compressed sensing is a novel technique where one can recover sparse signals from the undersampled measurements. In this paper, a $K \times N$ measurement matrix for compressed sensing is deterministically constructed via multiplicative…

Information Theory · Computer Science 2010-11-12 Nam Yul Yu

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

The complexity of computing the Lempel-Ziv factorization and the set of all runs (= maximal repetitions) is studied in the decision tree model of computation over ordered alphabet. It is known that both these problems can be solved by RAM…

Data Structures and Algorithms · Computer Science 2014-09-22 Dmitry Kosolobov

Consider the set of all sequences of $n$ outcomes, each taking one of $m$ values, that satisfy a number of linear constraints. If $m$ is fixed while $n$ increases, most sequences that satisfy the constraints result in frequency vectors…

Information Theory · Computer Science 2016-11-18 Kostas N. Oikonomou , Peter D. Grunwald

In grammar-based compression a string is represented by a context-free grammar, also called a straight-line program (SLP), that generates only that string. We refine a recent balancing result stating that one can transform an SLP of size…

Data Structures and Algorithms · Computer Science 2021-07-02 Moses Ganardi

It has been proven that, when normalized by $n$, the expected length of a longest common subsequence of $d$ random strings of length $n$ over an alphabet of size $\sigma$ converges to some constant that depends only on $d$ and $\sigma$.…

Data Structures and Algorithms · Computer Science 2024-07-16 George T. Heineman , Chase Miller , Daniel Reichman , Andrew Salls , Gábor Sárközy , Duncan Soiffer

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

In this paper, we resolve the one-pass space complexity of $L_p$ sampling for $p \in (0,2)$. Given a stream of updates (insertions and deletions) to the coordinates of an underlying vector $f \in \mathbb{R}^n$, a perfect $L_p$ sampler must…

Data Structures and Algorithms · Computer Science 2019-11-12 Rajesh Jayaram , David P. Woodruff

Compressed Counting (CC), based on maximally skewed stable random projections, was recently proposed for estimating the p-th frequency moments of data streams. The case p->1 is extremely useful for estimating Shannon entropy of data…

Data Structures and Algorithms · Computer Science 2009-10-09 Ping Li