arXiv:2510.27588v3 Announce Type: replace-cross Abstract: We consider the task of constructing a data structure for associating a static set of keys with values, while allowing arbitrary output values for queries involving keys outside the set. Compared to hash tables, these so-called static function data structures do not need to store the key set and thus use significantly less memory. Several techniques are known, with compressed static functions approaching the zero-order empirical entropy of the value sequence. In this paper, we introduce learned static functions, which use machine learni
Source: arXiv cs.LG — read the full report at the original publisher.