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Selective Weighted Adaptive Coding

Citation Author(s):
Gross, Klein, Opalinsky, Shapira
Submitted by:
Shmuel Klein
Last updated:
3 March 2022 - 5:32am
Document Type:
Poster
Document Year:
2022
Event:
Presenters:
Shmuel Klein
Categories:

Abstract

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Comments

So "Subset selective" means that you select a subset of characters for which you use a weighted coding, while the other characters are coded with the classic static coding?
I would appreciate if you can explain the "tuned" variant in more detail.
When talking about skip sizes f(s), you mean an equidistant selection of characters of a ranked alphabet,
meaning f(s) = k <=> the ranks of two selected characters are at a distance of at least k?
In that sense, the evaluated times following a geometric distribution seem plausible if updating the weights is the bottleneck in the computation.

Speaking about the time plots, can you explain what α is?
I assume that compression ratio is the fraction of the compressed file over the input length, so smaller ratio equals better compression.
Can I assume that the used test file is so small that a zeroth order entropy encoder such as Huffman can be better than gzip as seen on the left end of the left plot?

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