CUED Publications database

Improving PPM with Dynamic Parameter Updates

Steinruecken, C and Ghahramani, Z and MacKay, D (2015) Improving PPM with Dynamic Parameter Updates. In: UNSPECIFIED pp. 193-202..

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© 2015 IEEE. This article makes several improvements to the classic PPM algorithm, resulting in a new algorithm with superior compression effectiveness on human text. The key differences of our algorithm to classic PPM are that (A) rather than the original escape mechanism, we use a generalised blending method with explicit hyper-parameters that control the way symbol counts are combined to form predictions, (B) different hyper-parameters are used for classes of different contexts, and (C) these hyper-parameters are updated dynamically using gradient information. The resulting algorithm (PPM-DP) compresses human text better than all currently published variants of PPM, CTW, DMC, LZ, CSE and BWT, with runtime only slightly slower than classic PPM.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Divisions: Div F > Computational and Biological Learning
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 19:45
Last Modified: 17 May 2018 06:05