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DC Field | Value | Language |
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dc.contributor.author | Thongchai Dumrongpokaphan | en_US |
dc.contributor.author | Vladik Kreinovich | en_US |
dc.date.accessioned | 2018-09-05T04:26:21Z | - |
dc.date.available | 2018-09-05T04:26:21Z | - |
dc.date.issued | 2018-01-01 | en_US |
dc.identifier.issn | 1860949X | en_US |
dc.identifier.other | 2-s2.0-85038867695 | en_US |
dc.identifier.other | 10.1007/978-3-319-73150-6_6 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85038867695&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/58567 | - |
dc.description.abstract | © 2018, Springer International Publishing AG. In this paper, we show that, similarly to the fact that distributing the investment between several independent financial instruments decreases the investment risk, using a combination of several medicines can decrease the medicines’ side effects. Moreover, the formulas for optimal combinations of medicine are the same as the formulas for the optimal portfolio, formulas first derived by the Nobel-prize winning economist H. M. Markowitz. A similar application to machine learning explains a recent success of a modified neural network in which the input neurons are also directly connected to the output ones. | en_US |
dc.subject | Computer Science | en_US |
dc.title | Markowitz portfolio theory helps decrease medicines’ side effect and speed up machine learning | en_US |
dc.type | Book Series | en_US |
article.title.sourcetitle | Studies in Computational Intelligence | en_US |
article.volume | 760 | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
article.stream.affiliations | University of Texas at El Paso | en_US |
Appears in Collections: | CMUL: Journal Articles |
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