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Almost-Smooth Histograms and Sliding-Window Graph Algorithms
[article]
2022
arXiv
pre-print
We study algorithms for the sliding-window model, an important variant of the data-stream model, in which the goal is to compute some function of a fixed-length suffix of the stream. We extend the smooth-histogram framework of Braverman and Ostrovsky (FOCS 2007) to almost-smooth functions, which includes all subadditive functions. Specifically, we show that if a subadditive function can be (1+ϵ)-approximated in the insertion-only streaming model, then it can be (2+ϵ)-approximated also in the
arXiv:1904.07957v3
fatcat:4nisfdx7hjczdktls7wqdcuctq