{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,17]],"date-time":"2024-07-17T09:07:39Z","timestamp":1721207259723},"reference-count":5,"publisher":"Cambridge University Press (CUP)","issue":"2","license":[{"start":{"date-parts":[[2019,4,1]],"date-time":"2019-04-01T00:00:00Z","timestamp":1554076800000},"content-version":"unspecified","delay-in-days":31,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Nat. Lang. Eng."],"published-print":{"date-parts":[[2019,3]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>General Adversarial Networks are hot. Given Murphy\u2019s Law, it is prudent to be paranoid. Best not to design for the average case. There is a long tradition of designing for the hundred-year flood (and five 9s reliability). What is good enough? Historically, the market hasn\u2019t been willing to pay for five 9s. Hard to justify upfront costs for future benefits that will only payoff under unlikely scenarios, and might not work when needed. If the market isn\u2019t willing to pay for five 9s, can we afford to design for the worst case?<\/jats:p>","DOI":"10.1017\/s1351324919000020","type":"journal-article","created":{"date-parts":[[2019,4,1]],"date-time":"2019-04-01T10:22:07Z","timestamp":1554114127000},"page":"323-329","source":"Crossref","is-referenced-by-count":1,"title":["GANs vs. good enough"],"prefix":"10.1017","volume":"25","author":[{"given":"Kenneth Ward","family":"Church","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"56","published-online":{"date-parts":[[2019,4,1]]},"reference":[{"key":"S1351324919000020_ref5","doi-asserted-by":"publisher","DOI":"10.1109\/26.179938"},{"key":"S1351324919000020_ref4","unstructured":"Tsipras D. , Santurkar S. , Engstrom L. , Turner A. and Madry A. (2018). Robustness may be at odds with accuracy. arXiv:1805.12152."},{"key":"S1351324919000020_ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3052973.3053009"},{"key":"S1351324919000020_ref1","first-page":"387","volume-title":"Joint European Conference on Machine Learning and Knowledge Discovery in Databases","author":"Biggio","year":"2013"},{"key":"S1351324919000020_ref3","unstructured":"Szegedy C. , Zaremba W. , Sutskever I. , Bruna J. , Erhan D. , Goodfellow I. and Ferbus R. (2013). Intriguing properties of neural networks. arXiv:1312.6199."}],"container-title":["Natural Language Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S1351324919000020","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,4,12]],"date-time":"2019-04-12T00:36:58Z","timestamp":1555029418000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S1351324919000020\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,3]]},"references-count":5,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2019,3]]}},"alternative-id":["S1351324919000020"],"URL":"https:\/\/doi.org\/10.1017\/s1351324919000020","relation":{},"ISSN":["1351-3249","1469-8110"],"issn-type":[{"value":"1351-3249","type":"print"},{"value":"1469-8110","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,3]]}}}