Generalized Probability Smoothing
نویسنده
چکیده
In this work we consider a generalized version of Probability Smoothing, the core elementary model for sequential prediction in the state of the art PAQ family of data compression algorithms. Our main contribution is a code length analysis that considers the redundancy of Probability Smoothing with respect to a Piecewise Stationary Source. The analysis holds for a finite alphabet and expresses redundancy in terms of the total variation in probability mass of the stationary distributions of a Piecewise Stationary Source. By choosing parameters appropriately Probability Smoothing has redundancyO(S · √ T logT) for sequences of length T with respect to a Piecewise Stationary Source with S segments.
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عنوان ژورنال:
- CoRR
دوره abs/1712.02151 شماره
صفحات -
تاریخ انتشار 2017