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- W4283694872 abstract "One of the open problems in machine learning is whether any set-family of VC-dimension $d$ admits a sample compression scheme of size~$O(d)$. In this paper, we study this problem for balls in graphs. For balls of arbitrary radius $r$, we design proper sample compression schemes of size $2$ for trees, of size $3$ for cycles, of size $4$ for interval graphs, of size $6$ for trees of cycles, and of size $22$ for cube-free median graphs. For balls of a given radius, we design proper labeled sample compression schemes of size $2$ for trees and of size $4$ for interval graphs. We also design approximate sample compression schemes of size 2 for balls of $delta$-hyperbolic graphs." @default.
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- W4283694872 date "2022-06-27" @default.
- W4283694872 modified "2023-10-15" @default.
- W4283694872 title "Sample compression schemes for balls in graphs" @default.
- W4283694872 doi "https://doi.org/10.48550/arxiv.2206.13254" @default.
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