@inproceedings{bb68100b381043d190ef058498a83166,
title = "Optimal Synthesis of IDK-Cascades",
abstract = "A classifier is a software component, often based upon deep learning (DL), that categorizes each input provided to it into one of a fixed set of {"}classes{"}. An IDK classifier may additionally output an {"}I don't know{"}(IDK) on certain input. Given several different IDK classifiers for the same operation, the problem is considered of using them in concert in such a manner that the average duration to successfully classify any input is minimized. Optimal algorithms are proposed for solving this problem, both as is and under an additional constraint that the operation must be completed within a specified hard deadline).",
keywords = "Classifiers, Deep Learning, Hard deadlines, IDK-Cascades, Optimal Synthesis",
author = "Sanjoy Baruah and Alan Burns and Yue Wu",
note = "Publisher Copyright: {\textcopyright} 2021 ACM.; 29th International Conference on Real-Time Networks and Systems, RTNS 2021 ; Conference date: 07-04-2021",
year = "2021",
month = apr,
day = "7",
doi = "10.1145/3453417.3453425",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "184--191",
booktitle = "RTNS 2021 - 29th International Conference on Real-Time Networks and Systems",
}