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Robust Machine Learning Systems: Challenges,Current Trends, Perspectives, and the Road Ahead
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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Shafique, Muhammad | - |
| dc.contributor.author | Naseer, Mahum | - |
| dc.contributor.author | Theocharides, Theocharis | - |
| dc.contributor.author | Kyrkou, Christos | - |
| dc.contributor.author | Mutlu, Onur | - |
| dc.contributor.author | Orosa, Lois | - |
| dc.contributor.author | Choi, Jungwook | - |
| dc.date.accessioned | 2021-08-02T09:28:42Z | - |
| dc.date.available | 2021-08-02T09:28:42Z | - |
| dc.date.created | 2021-05-12 | - |
| dc.date.issued | 2020-04 | - |
| dc.identifier.issn | 2168-2356 | - |
| dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/9909 | - |
| dc.description.abstract | Currently, machine learning (ML) techniques are at the heart of smart cyber-physical systems (CPS) and Internet-of-Things (IoT). This article discusses various challenges and probable solutions for security attacks on these ML-inspired hardware and software techniques. -Partha Pratim Pande, Washington State University | - |
| dc.language | 영어 | - |
| dc.language.iso | en | - |
| dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
| dc.title | Robust Machine Learning Systems: Challenges,Current Trends, Perspectives, and the Road Ahead | - |
| dc.type | Article | - |
| dc.contributor.affiliatedAuthor | Choi, Jungwook | - |
| dc.identifier.doi | 10.1109/MDAT.2020.2971217 | - |
| dc.identifier.scopusid | 2-s2.0-85078838707 | - |
| dc.identifier.wosid | 000530237100005 | - |
| dc.identifier.bibliographicCitation | IEEE DESIGN & TEST, v.37, no.2, pp.30 - 57 | - |
| dc.relation.isPartOf | IEEE DESIGN & TEST | - |
| dc.citation.title | IEEE DESIGN & TEST | - |
| dc.citation.volume | 37 | - |
| dc.citation.number | 2 | - |
| dc.citation.startPage | 30 | - |
| dc.citation.endPage | 57 | - |
| dc.type.rims | ART | - |
| dc.type.docType | Article | - |
| dc.description.journalClass | 1 | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Computer Science | - |
| dc.relation.journalResearchArea | Engineering | - |
| dc.relation.journalWebOfScienceCategory | Computer Science, Hardware & Architecture | - |
| dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
| dc.subject.keywordPlus | DEEP NEURAL-NETWORKS | - |
| dc.subject.keywordPlus | ABSTRACTION-REFINEMENT | - |
| dc.subject.keywordPlus | MEMORY | - |
| dc.subject.keywordPlus | RELIABILITY | - |
| dc.subject.keywordPlus | ERRORS | - |
| dc.subject.keywordAuthor | Training data | - |
| dc.subject.keywordAuthor | Artificial neural networks | - |
| dc.subject.keywordAuthor | Reliability | - |
| dc.subject.keywordAuthor | Smart devices | - |
| dc.subject.keywordAuthor | Hardware | - |
| dc.subject.keywordAuthor | Machine learning | - |
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Related Researcher
- Choi, Jung wook
- COLLEGE OF ENGINEERING (SCHOOL OF ELECTRONIC ENGINEERING)