@inproceedings{0100c262b275480bbac33728ee358926,
title = "Learning Disjunctions of Predicates",
abstract = "Let $ be a set of boolean functions. We give an algorithm for learning $∨:=f∈Sf | S⊆F$ from membership queries. Our algorithm asks at most $|F|⋅F_∨)$ membership queries where $F_∨)$ is the minimum worst case number of membership queries for learning $F_∨$. When $F$ is a set of halfspaces over a constant dimension space or a set of variable inequalities, our algorithm runs in polynomial time. The problem we address has a practical importance in the field of program synthesis, where the goal is to synthesize a program meeting some requirements. Program synthesis has become popular especially in settings aimed to help end users. In such settings, the requirements are not provided upfront and the synthesizer can only learn them by posing membership queries to the end user. Our work completes such synthesizers with the ability to learn the exact requirements while bounding the number of membership queries.",
author = "Bshouty, {Nader H.} and Dana Drachsler-Cohen and Martin Vechev and Eran Yahav",
year = "2017",
month = jul,
day = "1",
language = "الإنجليزيّة",
volume = "65",
series = "Proceedings of Machine Learning Research",
publisher = "PMLR",
pages = "346--369",
editor = "Satyen Kale and Ohad Shamir",
booktitle = "Proceedings of the 2017 Conference on Learning Theory",
}