Lossless data compression with transformer

  • Can lossless files be compressed?

    Lossless compression is possible because, in general, there is significant redundancy present in image signals.
    This redundancy is proportional to the amount of correlation among the image data samples..

  • How lossless compression compresses the text file?

    Lossless compression methods reduce the size of text files by finding patterns or repetitions in the information and encoding them more efficiently.
    For example, some lossless methods use dictionary-based or statistical methods to replace frequent or long sequences of characters with shorter codes..

  • What are two methods of lossless compression?

    The algorithms used in lossless compression are:

    Run Length Encoding.Lempel-Ziv-Welch (LZW)Huffman Coding.Arithmetic Encoding..

  • What is the best lossless image compression?

    FLIF is a novel lossless image format which outperforms PNG, lossless WebP, lossless BPG, lossless JPEG2000, and lossless JPEG XR in terms of compression ratio..

  • What is the most efficient lossless compression?

    The best lossless compression algorithm may not be the same in every case.
    One of the most popular is Run-Length Encoding (RLE), which encodes data into smaller bytes by identifying repeated information..

  • What is the principle of lossless compression?

    Lossless compression is a class of data compression that allows the original data to be perfectly reconstructed from the compressed data with no loss of information.
    Lossless compression is possible because most real-world data exhibits statistical redundancy..

  • Which of the following is a lossless data compression?

    Deflate is a lossless data compression algorithm and associated file format that uses a combination of the LZ77 algorithm and Huffman coding.
    An algorithm producing deflate files is widely thought to be implementable in a manner not covered by patents..

  • Lossless compression is used in cases where it is important that the original and the decompressed data be identical, or where deviations from the original data would be unfavourable.
    Common examples are executable programs, text documents, and source code.
  • On the other hand, PNG uses lossless compression.
    In this method, no data is deleted during the compression process.
    Instead, the algorithm finds efficient ways to represent the same data, resulting in an image that's identical to the original after decompression.
Sep 25, 2019In this paper, we propose a Transformer based lossless compression method that match the best compression ratio for text. Our approach is purely  Lossless Compression for Fast and Memory-Efficient Deep Neural Transformer-based Transform Coding - OpenReviewMore results from openreview.net
Sep 25, 2019In this paper, we propose a Transformer based lossless compression method that match the best compression ratio for text. Our approach is purely  Transformer-based Transform Coding - OpenReviewLossless Compression for Fast and Memory-Efficient Deep Neural More results from openreview.net

Can a single-layer transformer be a compression-friendly compressor?

However, existing transformer is too heavy in computation and incompatible to compression tasks.
This paper proposes a fast general-purpose lossless compressor, TRACE, by designing a compression-friendly structure based on a single-layer transformer.
We first design a new metric to advise the selection part of compression model structures.

,

Is NNCP a lossless data compression based on neural network models?

This article is a follow-up of where we presented NNCP, a lossless data compres- sor based on neural network models.
The NNCP Transformer model was improved so that it achieves better compression ratios at the expense of a larger computa- tional cost.

,

Who wrote a book on compressive transformers for long-range sequence modelling?

Jack W Rae, Anna Potapenko, Siddhant M Jayakumar, and Timothy P Lillicrap. 2019.
Compressive transformers for long-range sequence modelling. arXiv preprint arXiv:1911.05507 (2019).
Claude Elwood Shannon. 1948.
A mathematical theory of communication.
The Bell system technical journal 27, 3 (1948), 379–423.
Rajeev Sharma. 2016.

,

Why was the NNCP transformer model improved?

The NNCP Transformer model was improved so that it achieves better compression ratios at the expense of a larger computa- tional cost.
The model parameters were chosen so that it is possible to achieve the published results on a personal computer with a single GPU in a few days.

Can a single-layer transformer be a compression-friendly compressor?

However, existing transformer is too heavy in computation and incompatible to compression tasks

This paper proposes a fast general-purpose lossless compressor, TRACE, by designing a compression-friendly structure based on a single-layer transformer

We first design a new metric to advise the selection part of compression model structures

Is NNCP a lossless data compression based on neural network models?

This article is a follow-up of where we presented NNCP, a lossless data compres- sor based on neural network models

The NNCP Transformer model was improved so that it achieves better compression ratios at the expense of a larger computa- tional cost

Why was the NNCP transformer model improved?

The NNCP Transformer model was improved so that it achieves better compression ratios at the expense of a larger computa- tional cost

The model parameters were chosen so that it is possible to achieve the published results on a personal computer with a single GPU in a few days


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