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The random access problem for compressed strings is to build a data structure that efficiently supports accessing the character in position $i$ of a string given in compressed form. Given a grammar of size $n$ compressing a string of size…

Data Structures and Algorithms · Computer Science 2015-01-27 Patrick Hagge Cording

We study whether, when restricted to using polylogarithmic memory and polylogarithmic passes, we can achieve qualitatively better data compression with multiple read/write streams than we can with only one. We first show how we can achieve…

Data Structures and Algorithms · Computer Science 2012-04-06 Travis Gagie

We investigate the information complexity of mixed-integer convex optimization under different types of oracles. We establish new lower bounds for the standard first-order oracle, improving upon the previous best known lower bound. This…

Optimization and Control · Mathematics 2023-08-23 Amitabh Basu , Hongyi Jiang , Phillip Kerger , Marco Molinaro

A central question in information theory is to determine the maximum success probability that can be achieved in sending a fixed number of messages over a noisy channel. This was first studied in the pioneering work of Shannon who…

Information Theory · Computer Science 2018-06-25 Siddharth Barman , Omar Fawzi

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

Motivated by a popular code golf challenge, we review some key ideas from information theory and discuss how to efficiently compress a streaming file with an acceptable error rate.

Information Theory · Computer Science 2025-02-04 Boris Alexeev , Dustin G. Mixon

Neural compression is the application of neural networks and other machine learning methods to data compression. Recent advances in statistical machine learning have opened up new possibilities for data compression, allowing compression…

Machine Learning · Computer Science 2023-08-22 Yibo Yang , Stephan Mandt , Lucas Theis

Real-world data typically contain repeated and periodic patterns. This suggests that they can be effectively represented and compressed using only a few coefficients of an appropriate basis (e.g., Fourier, Wavelets, etc.). However, distance…

Machine Learning · Statistics 2014-05-26 Michail Vlachos , Nikolaos Freris , Anastasios Kyrillidis

The purpose of this paper is to answer two questions left open in [B. Durand, A. Shen, and N. Vereshchagin, Descriptive Complexity of Computable Sequences, Theoretical Computer Science 171 (2001), pp. 47--58]. Namely, we consider the…

Logic · Mathematics 2019-02-05 Nikolay Vereshchagin

The number of zeros and the number of ones in a binary string are referred to as the composition of the string, and the prefix-suffix compositions of a string are a multiset formed by the compositions of the prefixes and suffixes of all…

Information Theory · Computer Science 2025-03-18 Zitan Chen

Integer-forcing source coding has been proposed as a low-complexity method for compression of distributed correlated Gaussian sources. In this scheme, each encoder quantizes its observation using the same fine lattice and reduces the result…

Information Theory · Computer Science 2019-06-05 Elad Domanovitz , Uri Erez

Compression refers to encoding data using bits, so that the representation uses as few bits as possible. Compression could be lossless: i.e. encoded data can be recovered exactly from its representation) or lossy where the data is…

Information Theory · Computer Science 2012-10-19 Narayana Santhanam , Dharmendra Modha

There is a common problem of operating on hash values of elements of some database. In this paper there will be analyzed informational content of such general task and how to practically approach such found lower boundaries. Minimal prefix…

Information Theory · Computer Science 2012-07-10 Jarek Duda

We analyze software reuse from the perspective of information theory and Kolmogorov complexity, assessing our ability to ``compress'' programs by expressing them in terms of software components reused from libraries. A common theme in the…

Software Engineering · Computer Science 2016-08-31 Todd L. Veldhuizen

It was recently shown that the lossless compression of a single source $X^n$ is achievable with a notion of strong locality; any $X_i$ can be decoded from a constant number of compressed bits, with a vanishing in $n$ probability of error.…

Information Theory · Computer Science 2022-09-28 Shashank Vatedka , Venkat Chandar , Aslan Tchamkerten

We study the problem of extracting a small subset of representative items from a large data stream. In many data mining and machine learning applications such as social network analysis and recommender systems, this problem can be…

Data Structures and Algorithms · Computer Science 2021-02-15 Yanhao Wang , Francesco Fabbri , Michael Mathioudakis

A set is introreducible if it can be computed by every infinite subset of itself. Such a set can be thought of as coding information very robustly. We investigate introreducible sets and related notions. Our two main results are that the…

Logic · Mathematics 2020-11-09 Noam Greenberg , Matthew Harrison-Trainor , Ludovic Patey , Dan Turetsky

We investigate topological, combinatorial, statistical, and enumeration properties of finite graphs with high Kolmogorov complexity (almost all graphs) using the novel incompressibility method. Example results are: (i) the mean and variance…

Combinatorics · Mathematics 2007-05-23 Harry Buhrman , Ming Li , John Tromp , Paul Vitanyi

Shannon entropy is the shortest average codeword length a lossless compressor can achieve by encoding i.i.d. symbols. However, there are cases in which the objective is to minimize the \textit{exponential} average codeword length, i.e. when…

Information Theory · Computer Science 2024-06-10 Andrea Somazzi , Paolo Ferragina , Diego Garlaschelli

This paper deals with the two fundamental problems concerning the handling of large n-gram language models: indexing, that is compressing the n-gram strings and associated satellite data without compromising their retrieval speed; and…

Information Retrieval · Computer Science 2022-02-08 Giulio Ermanno Pibiri , Rossano Venturini