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Uncertain < T > : A first-order type for uncertain data

Bornholt, James; Mytkowicz, Todd; McKinley, Kathryn


Emerging applications increasingly use estimates such as sensor data (GPS), probabilistic models, machine learning, big data, and human data. Unfortunately, representing this uncertain data with discrete types (floats, integers, and booleans) encourages developers to pretend it is not probabilistic, which causes three types of uncertainty bugs. (1) Using estimates as facts ignores random error in estimates. (2) Computation compounds that error. (3) Boolean questions on probabilistic data induce...[Show more]

CollectionsANU Research Publications
Date published: 2014
Type: Conference paper
Source: International Conference on Architectural Support for Programming Languages and Operating Systems - ASPLOS
DOI: 10.1145/2541940.2541958


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