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Preprints, Working Papers, ... Year : 2017

Learning Monotone Partitions of Partially-Ordered Domains (Work in Progress)

Oded Maler
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Abstract

We present an algorithm for learning the boundary between an upward-closed set X and its downward-closed complement. The algorithm selects sampling points for which it submits membership queries x ∈ X. Based on the answers and relying on monotonicity, it constructs an approximation of the boundary. The algorithm generalizes binary search on the continuum from one-dimensional (and linearly-ordered) domains to multi-dimensional (and partially-ordered) ones. Applications include the approximation of Pareto fronts in multi-criteria optimization and parameter synthesis for predicates where the influence of parameters is monotone.
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Dates and versions

hal-01556243 , version 1 (04-07-2017)

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  • HAL Id : hal-01556243 , version 1

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Oded Maler. Learning Monotone Partitions of Partially-Ordered Domains (Work in Progress). 2017. ⟨hal-01556243⟩
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