@inproceedings{4d2642e9dde9427b863df85993b02125,
title = "Feedback Control for Binary Response",
abstract = "Defect rate control is crucial in industries. When binary response is considered, the defect rate is the average of these binary responses. In this study, with logistic regression model and sparsity assumption, the feedback control problem is expressed as an optimization problem which solves a hinge loss with an L1 penalty. Here the hinge loss function is substituted for the Huberized hinge loss to avoid discontinuity caused by the L1 penalty, and the majorization-minimization principle is applied to enhance computing efficiency. Then the coordinate descent algorithm is implemented for sparse estimation. Several examples and a real data example are used to illustrate the performance of the proposed feedback control procedure.",
author = "Chen, {Ping Yang} and Hsia, {Chi Chun} and Su, {Yen Hao} and Chen, {Ray Bing} and Chang, {Sheng Mao}",
year = "2018",
month = may,
day = "9",
doi = "10.1109/TAAI.2017.23",
language = "English",
series = "Proceedings - 2017 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "21--24",
booktitle = "Proceedings - 2017 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2017",
address = "United States",
note = "2017 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2017 ; Conference date: 01-12-2017 Through 03-12-2017",
}