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Applications of MaxSAT in Data Analysis

15 pagesPublished: March 15, 2019

Abstract

We highlight important real-world optimization problems arising from data analysis and machine learning, representing somewhat atypical applications of SAT-based solver technology, to which the SAT community could focus more attention on. To address the problem of current lack of heterogeneity in benchmark sets available for evaluating MaxSAT solvers, we provide a benchmark library of MaxSAT instances encoding different data analysis and machine learning problems. By doing so, we also advocate extending MaxSAT solvers to accept real-valued weights for soft clauses as input via the presented problem domains in which the use of real-valued costs plays an integral role.

In: Daniel Le Berre and Matti Järvisalo (editors). Proceedings of Pragmatics of SAT 2015 and 2018, vol 59, pages 50--64

Links:
BibTeX entry
@inproceedings{POS-18:Applications_of_MaxSAT_in,
  author    = {Jeremias Berg and Antti Hyttinen and Matti J\textbackslash{}"arvisalo},
  title     = {Applications of MaxSAT in Data Analysis},
  booktitle = {Proceedings of Pragmatics of SAT 2015 and 2018},
  editor    = {Daniel Le Berre and Matti J\textbackslash{}"arvisalo},
  series    = {EPiC Series in Computing},
  volume    = {59},
  pages     = {50--64},
  year      = {2019},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {https://easychair.org/publications/paper/6HpF},
  doi       = {10.29007/3qkh}}
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