Computing Minimax Decisions with Incomplete Observations

Open Access
Authors
Publication date 2017
Journal Proceedings of Machine Learning Research
Event 10th International Symposium on Imprecise Probability: Theories and Applications
Volume | Issue number 62
Pages (from-to) 358-369
Number of pages 12
Organisations
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
Abstract Decision makers must often base their decisions on incomplete (coarse) data. Recent research has shown that in a wide variety of coarse data problems, minimax optimal strategies can be recognized using a simple probabilistic condition. This paper develops a computational method to find such strategies in special cases, and shows what difficulties may arise in more general cases.
Document type Article
Note Proceedings of the Tenth International Symposium on Imprecise Probability: Theories and Applications, 10-14 July 2017 (ISIPTA'17)
Language English
Published at http://proceedings.mlr.press/v62/van-ommen17a.html
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