A new algorithm computes Re-Pair, a grammar-based compression method, in O(n^2) time using roughly text-sized working space, but the core frequency-counting proof appears to overcount repeated-character bigrams.
The smallest grammar problem revisited
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
In a seminal paper of Charikar et al. on the smallest grammar problem, the authors derive upper and lower bounds on the approximation ratios for several grammar-based compressors, but in all cases there is a gap between the lower and upper bound. Here the gaps for $\mathsf{LZ78}$ and $\mathsf{BISECTION}$ are closed by showing that the approximation ratio of $\mathsf{LZ78}$ is $\Theta( (n/\log n)^{2/3})$, whereas the approximation ratio of $\mathsf{BISECTION}$ is $\Theta(\sqrt{n/\log n})$. In addition, the lower bound for $\mathsf{RePair}$ is improved from $\Omega(\sqrt{\log n})$ to $\Omega(\log n/\log\log n)$. Finally, results of Arpe and Reischuk relating grammar-based compression for arbitrary alphabets and binary alphabets are improved.
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cs.DS 1years
2019 1verdicts
REJECT 1representative citing papers
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Re-Pair In Small Space
A new algorithm computes Re-Pair, a grammar-based compression method, in O(n^2) time using roughly text-sized working space, but the core frequency-counting proof appears to overcount repeated-character bigrams.