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Traditionally, data compression deals with the problem of concisely representing a data source, e.g. a sequence of letters, for the purpose of eventual reproduction (either exact or approximate). In this work we are interested in the case…

Information Theory · Computer Science 2013-12-10 Amir Ingber , Tsachy Weissman

We describe a method for lossless quantum compression if the output of the information source is not known. We compute the best possible compression rate, minimizing the expected base length of the output quantum bit string (the base length…

Quantum Physics · Physics 2009-01-19 Markus Mueller , Caroline Rogers , Rajagopal Nagarajan

In a distributed information application an encoder compresses an arbitrary vector while a similar reference vector is available to the decoder as side information. For the Hamming-distance similarity measure, and when guaranteed perfect…

Information Theory · Computer Science 2020-09-08 Yuval Cassuto , Jacob Ziv

The problem of lossless data compression with side information available to both the encoder and the decoder is considered. The finite-blocklength fundamental limits of the best achievable performance are defined, in two different versions…

Information Theory · Computer Science 2021-02-23 Lampros Gavalakis , Ioannis Kontoyiannis

Secure data compression in the presence of side information at both a legitimate receiver and an eavesdropper is explored. A noise-free, limited rate link between the source and the receiver, whose output can be perfectly observed by the…

Information Theory · Computer Science 2016-11-17 Deniz Gunduz , Elza Erkip , H. Vincent Poor

Compressing the output of \epsilon-locally differentially private (LDP) randomizers naively leads to suboptimal utility. In this work, we demonstrate the benefits of using schemes that jointly compress and privatize the data using shared…

Cryptography and Security · Computer Science 2022-03-01 Abhin Shah , Wei-Ning Chen , Johannes Balle , Peter Kairouz , Lucas Theis

Suppose that a quantum source is known to have von Neumann entropy less than or equal to S but is otherwise completely unspecified. We describe a method of universal quantum data compression which will faithfully compress the quantum…

Quantum Physics · Physics 2009-10-31 Richard Jozsa , Michal Horodecki , Pawel Horodecki , Ryszard Horodecki

We consider the problem of source compression under three different scenarios in the one-shot (non- asymptotic) regime. To be specific, we prove one-shot achievability and converse bounds on the coding rates for distributed source coding,…

Information Theory · Computer Science 2015-12-11 Naqueeb Ahmad Warsi

We present new lower and upper bounds for the compression rate of binary prefix codes optimized over memoryless sources according to two related exponential codeword length objectives. The objectives explored here are exponential-average…

Information Theory · Computer Science 2011-05-03 Michael B. Baer

This article describes lossless compression algorithms for multisets of sequences, taking advantage of the multiset's unordered structure. Multisets are a generalisation of sets where members are allowed to occur multiple times. A multiset…

Information Theory · Computer Science 2014-01-27 Christian Steinruecken

In this paper, we consider the one-shot version of the classical Wyner-Ziv problem where a source is compressed in a lossy fashion when only the decoder has access to a correlated side information. Following the entropy-constrained…

Information Theory · Computer Science 2024-05-06 Oğuzhan Kubilay Ülger , Elza Erkip

This paper describes a new method of data encoding which may be used in various modern digital, computer and telecommunication systems and devices. The method permits the compression of data for storage or transmission, allowing the exact…

Information Theory · Computer Science 2012-01-27 Igor Nesiolovskiy , Artem Nesiolovskiy

The goal of lossy data compression is to reduce the storage cost of a data set $X$ while retaining as much information as possible about something ($Y$) that you care about. For example, what aspects of an image $X$ contain the most…

Machine Learning · Computer Science 2020-01-16 Max Tegmark , Tailin Wu

Sorted data is usually easier to compress than unsorted permutations of the same data. This motivates a simple compression scheme: specify the sorted permutation of the data along with a representation of the sorted data compressed…

Data Structures and Algorithms · Computer Science 2014-11-24 Oscar Stiffelman

Large alphabet source coding is a basic and well-studied problem in data compression. It has many applications such as compression of natural language text, speech and images. The classic perception of most commonly used methods is that a…

Information Theory · Computer Science 2016-07-26 Amichai Painsky , Saharon Rosset , Meir Feder

A classical random variable can be faithfully compressed into a sequence of bits with its expected length lies within one bit of Shannon entropy. We generalize this variable-length and faithful scenario to the general quantum source…

Quantum Physics · Physics 2009-11-07 Masato Koashi , Nobuyuki Imoto

Compression of integer sets and sequences has been extensively studied for settings where elements follow a uniform probability distribution. In addition, methods exist that exploit clustering of elements in order to achieve higher…

Information Theory · Computer Science 2014-02-11 N. Jesper Larsson

The idea that compressed sensing may be used to encrypt information from unauthorised receivers has already been envisioned, but never explored in depth since its security may seem compromised by the linearity of its encoding process. In…

Information Theory · Computer Science 2015-03-02 Valerio Cambareri , Mauro Mangia , Fabio Pareschi , Riccardo Rovatti , Gianluca Setti

Variable-length compression without prefix-free constraints and with side-information available at both encoder and decoder is considered. Instead of requiring the code to be error-free, we allow for it to have a non-vanishing error…

Information Theory · Computer Science 2020-08-24 Yuta Sakai , Vincent Y. F. Tan

Most data is automatically collected and only ever "seen" by algorithms. Yet, data compressors preserve perceptual fidelity rather than just the information needed by algorithms performing downstream tasks. In this paper, we characterize…

Machine Learning · Computer Science 2022-01-31 Yann Dubois , Benjamin Bloem-Reddy , Karen Ullrich , Chris J. Maddison