Arithmetic coding for data compression

By Ian H. Witten, Radford M. Neal, J. Cleary. 1987

Subfields: Optimization & Training, Information Theory

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Citations in the corpus

Towards Conceptual Compression (2016, background): “The underlying compression mechanism for all cases is arithmetic coding (Witten et al., 1987).”
Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations (2017, methodology): “However, our objective is to learn network parameters W that minimize (6) when using the encoder and decoder with hard assignments, such that we obtain a compressible symbol stream E ( z ) which we can compress using, e.g. , arithmetic coding [40].”
Cascaded Cross-Module Residual Learning towards Lightweight End-to-End Speech Coding (2019, background): “, the softmax result) separately, encoding short sequences can further leverage the temporal correlation in the series of quantized symbols, especially when the entropy is already low [29] [30].”
Compress and Control (2014, methodology): “A fundamental technique known as arithmetic encoding (Witten, Neal, and Cleary 1987) makes explicit the connection between coding distributions and source codes.”
The H.264/AVC Advanced Video Coding standard: overview and introduction to the fidelity range extensions (2004, methodology): “The arithmetic coding is largely based on the well-known techniques developed in [8].”
this paper (2009, unknown): “Finally, we report the A/B test results and the deployment progress of AFR on our cloud gaming service online (§6.5).”
Partial encryption of compressed images and videos (2000, background): “[34], and the compression performance is 2% worse than that of the original algorithm.”
Indexing Compressed Text (2003, methodology): “text compression with arithmetic coding, and we followed the implementation in [62].”
Wavelets and their applications (2007, methodology): “This method, allied to Huffman type coding or semiarithmetic or arithmetic codings [HUF 52], [AHO 87], [MAL 98], [WIT 87], [HOW 92], leads to satisfactory compression performances, comparable with those of JPEG 92.”
Information Theory, Inference, and Learning Algorithms (2004, methodology): “These defects are rectified by arithmetic codes, which were invented by Elias, by Rissanen and by Pasco, and subsequently made practical by Witten et al. (1987). In an arithmetic code, the probabilistic modelling is clearly separated from the encoding operation.”
Surprisal-Triggered Conditional Computation with Neural Networks (2020, background): “In arithmetic coding, less effort is allocated to less surprising inputs, in the sense that shorter bitstrings (less bandwidth) are assigned to more predictable symbols [58, 59].”
Learning Convolutional Networks for Content-Weighted Image Compression (2017, unknown): “Huffman tree and arithmetic coding [30].”
Data compression algorithms for energy-constrained devices in delay tolerant networks (2006, background): “In more traditional arenas, a large variety of compression algorithms have been proposed including string-based techniques [19][32][43], entropy-based tec hniques [11][15][40], and others.”
Context Tree Switching (2011, methodology): “Provided the data generating source is known, near optimal redundancy can essentially be achieved by using arithmetic encoding [Witten et al., 1987].”
The zero-frequency problem: Estimating the probabilities of novel events in adaptive text compression (1991, methodology): “Arithmetic coding provides a way of coding tokens with respect to a probability distribution in an optimal way; an accessible implementation of the technique can be found in [ 7 ].”
Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent Variables (2019, unknown): “Arithmetic Coding (AC) (Witten et al., 1987) 2.”