Learning MAX-SAT from contextual examples for combinatorial optimisation
From MaRDI portal
Publication:2680761
DOI10.1016/j.artint.2022.103794OpenAlexW4304893450MaRDI QIDQ2680761
Mohit Kumar, Stefano Teso, Luc De Raedt, Samuel Kolb
Publication date: 4 January 2023
Published in: Artificial Intelligence (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2202.03888
machine learningmaximum satisfiabilitycombinatorial optimisationsoft constraintsconstraint learningcontextual examples
Related Items (1)
Uses Software
Cites Work
- Structured learning modulo theories
- PySAT: a Python toolkit for prototyping with SAT oracles
- Modeling and solving staff scheduling with partial weighted maxSAT
- Automatic synthesis of constraints from examples using mixed integer linear programming
- Guided local search for solving SAT and weighted MAX-SAT problems
- Markov logic networks
- Learning MAX-SAT from contextual examples for combinatorial optimisation
- A note on bounds for VC dimensions
- Iterative Learning of Answer Set Programs from Context Dependent Examples
- Prediction, Learning, and Games
- Understanding Machine Learning
- A general scheme for automatic generation of search heuristics from specification \(dependencies^{*}\)
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
This page was built for publication: Learning MAX-SAT from contextual examples for combinatorial optimisation
