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Related papers: Local Decode and Update for Big Data Compression

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This paper addresses the problem of data compression with local decoding and local update. A compression scheme has worst-case local decoding $d_{wc}$ if any bit of the raw file can be recovered by probing at most $d_{wc}$ bits of the…

Information Theory · Computer Science 2020-01-24 Shashank Vatedka , Venkat Chandar , Aslan Tchamkerten

Motivated by distributed storage applications, we investigate the degree to which capacity achieving encodings can be efficiently updated when a single information bit changes, and the degree to which such encodings can be efficiently…

Information Theory · Computer Science 2013-10-08 Arya Mazumdar , Venkat Chandar , Gregory W. Wornell

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

In this paper we investigate the role of local information in the decoding of the repetition and surface error correction codes for the protection of quantum states. Our key result is an improvement in resource efficiency when local…

Quantum Physics · Physics 2020-06-30 Michael Hanks , William J. Munro , Kae Nemoto

Locally decodable channel codes form a special class of error-correcting codes with the property that the decoder is able to reconstruct any bit of the input message from querying only a few bits of a noisy codeword. It is well known that…

Information Theory · Computer Science 2013-08-28 Ali Makhdoumi , Shao-Lun Huang , Muriel Medard , Yury Polyanskiy

We initiate a study of locally decodable codes with randomized encoding. Standard locally decodable codes are error correcting codes with a deterministic encoding function and a randomized decoding function, such that any desired message…

Information Theory · Computer Science 2020-01-14 Kuan Cheng , Xin Li , Yu Zheng

In this paper, we investigate a coupled polar code architecture that supports both local and global decoding. This local-global construction is motivated by practical applications in data storage and transmission where reduced-latency…

Information Theory · Computer Science 2023-01-09 Ziyuan Zhu , Wei Wu , Paul H. Siegel

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

Consider a distributed coding for computing problem with constant decoding locality, i.e., with a vanishing error probability, any single sample of the function can be approximately recovered by probing only constant number of compressed…

Information Theory · Computer Science 2024-03-01 Deheng Yuan , Tao Guo , Zhongyi Huang , Shi Jin

Data deduplication saves storage space by identifying and removing repeats in the data stream. Compared with traditional compression methods, data deduplication schemes are more time efficient and are thus widely used in large scale storage…

Information Theory · Computer Science 2022-05-30 Hao Lou , Farzad Farnoud

We investigate dense coding by imposing various locality restrictions to our decoder by employing the resource theory of asymmetry framework. In this task, the sender Alice and the receiver Bob share an entangled state. She encodes the…

Quantum Physics · Physics 2024-09-10 Masahito Hayashi , Kun Wang

An index code for broadcast channel with receiver side information is locally decodable if each receiver can decode its demand by observing only a subset of the transmitted codeword symbols instead of the entire codeword. Local decodability…

Information Theory · Computer Science 2020-07-31 Lakshmi Natarajan , Prasad Krishnan , V. Lalitha , Hoang Dau

Data compression has been widely applied in many data processing areas. Compression methods use variable-size codes with the shorter codes assigned to symbols or groups of symbols that appear in the data frequently. Fibonacci coding, as a…

Performance · Computer Science 2007-12-19 R. Baca , V. Snasel , J. Platos , M. Kratky , E. El-Qawasmeh

We consider a variable-length source coding problem subject to local decodability constraints. In particular, we investigate the blocklength scaling behavior attainable by encodings of $r$-sparse binary sequences, under the constraint that…

Information Theory · Computer Science 2015-04-09 Ashwin Pananjady , Thomas A. Courtade

The problem of storing permutations in a distributed manner arises in several common scenarios, such as efficient updates of a large, encrypted, or compressed data set. This problem may be addressed in either a combinatorial or a coding…

Information Theory · Computer Science 2016-05-05 Netanel Raviv , Eitan Yaakobi , Muriel Medard

We study the problem of compressing a source sequence in the presence of side-information that is related to the source via insertions, deletions and substitutions. We propose a simple algorithm to compress the source sequence when the…

Information Theory · Computer Science 2016-11-15 Nan Ma , Kannan Ramchandran , David Tse

An index code is said to be locally decodable if each receiver can decode its demand using its side information and by querying only a subset of the transmitted codeword symbols instead of observing the entire codeword. Local decodability…

Information Theory · Computer Science 2019-01-18 Lakshmi Natarajan , Hoang Dau , Prasad Krishnan , V. Lalitha

This paper presents a theoretical study of a new type of LDPC codes motivated by practical storage applications. LDPCL codes (suffix L represents locality) are LDPC codes that can be decoded either as usual over the full code block, or…

Information Theory · Computer Science 2019-05-13 Eshed Ram , Yuval Cassuto

In this paper, we present a novel approach for fine-tuning a decoder-side neural network in the context of image compression, such that the weight-updates are better compressible. At encoder side, we fine-tune a pre-trained artifact removal…

Machine Learning · Computer Science 2019-06-17 Yat Hong Lam , Alireza Zare , Caglar Aytekin , Francesco Cricri , Jani Lainema , Emre Aksu , Miska Hannuksela

The ever-growing size of neural networks poses serious challenges on resource-constrained devices, such as embedded sensors. Compression algorithms that reduce their size can mitigate these problems, provided that model performance stays…

Machine Learning · Computer Science 2025-05-27 Alexander Conzelmann , Robert Bamler
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