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arXiv Machine Learning By Vanessa Kosoy

Stringological sequence prediction III: layered ziplines and a tradeoff between efficiency and expressivity

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The paper introduces a new complexity measure, based on a restricted class of "layered zipline programs," which is weaker than the previously defined Arithmetic Repetition Complexity (ARC). This measure allows for a prediction algorithm that operates in quasilinear time and polylogarithmic space on highly-structured sequences, offering a more efficient solution at the cost of reduced expressivity compared to ARC. The work highlights a tradeoff between algorithmic efficiency and the breadth of sequences that can be effectively predicted.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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