GT Heineman, C Miller, D Reichman, A Salls… - arXiv preprint arXiv …, 2024 - arxiv.org
It has been proven that, when normalized by $ n $, the expected length of a longest common subsequence of $ d $ random strings of length $ n $ over an alphabet of size $\sigma …
We consider the classic 1-center problem: Given a set $ P $ of $ n $ points in a metric space find the point in $ P $ that minimizes the maximum distance to the other points of $ P $. We …
In this paper we present $ LCSk $++: a new metric for measuring the similarity of long strings, and provide an algorithm for its efficient computation. With ever increasing size of …
M Rosenfeld - arXiv preprint arXiv:2407.18113, 2024 - arxiv.org
We study the average edit distance between two random strings. More precisely, we adapt a technique introduced by Lueker in the context of the average longest common subsequence …
The length of the longest common subsequences (LCSs) is often used as a similarity measurement to compare two (or more) random words. Below we study its statistical …
G Bilardi, M Schimd - arXiv preprint arXiv:2211.07644, 2022 - arxiv.org
The edit distance is a metric of dissimilarity between strings, widely applied in computational biology, speech recognition, and machine learning. Let $ e_k (n) $ denote the average edit …
C Houdré, Q Liu - arXiv preprint arXiv:1812.09552, 2018 - arxiv.org
We investigate the variance of the length of the longest common subsequences of two independent random words of size $ n $, where the letters of one word are iid uniformly …
B Bukh, Z Dong - arXiv preprint arXiv:2009.05869, 2020 - arxiv.org
We consider the expected length of the longest common subsequence between two random words of lengths $ n $ and $(1-\varepsilon) kn $ over $ k $-symbol alphabet. It is well-known …
In this thesis, we study several problems from combinatorial probability theory, discrete geometry and extremal graph theory. We establish several extremal results towards our …