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Compressing Multisets with Large Alphabets

Citation Author(s):
Daniel Severo, James Townsend, Ashish Khisti, Alireza Makhzani, Karen Ullrich
Submitted by:
Daniel Severo
Last updated:
5 March 2022 - 7:51pm
Document Type:
Presentation Slides
Document Year:
2022
Event:
Presenters:
Daniel Severo and James Townsend
Paper Code:
https://github.com/facebookresearch/multiset-compression
Categories:
Keywords:

Abstract

Current methods which compress multisets at an optimal rate have computational complexity that scales linearly with alphabet size, making them too slow to be practical in many real-world settings. We show how to convert a compression algorithm for sequences into one for multisets, in exchange for an additional complexity term that is quasi-linear in sequence length. This allows us to compress multisets of independent and identically distributed symbols at an optimal rate, with computational complexity decoupled from the alphabet size. The key insight is to avoid encoding the multiset directly, and instead compress a proxy sequence, using a technique called `bits-back coding'. We demonstrate the method experimentally on two tasks which are intractable with previous optimal-rate methods: compression of multisets of images and JavaScript Object Notation (JSON) files. Code for our experiments is available at https://github.com/facebookresearch/multiset-compression.

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