Research for Practice: Cryptocurrencies, Blockchains, and Smart Contracts; Hardware for Deep Learning.
The article provides information on academic research of cryptocurrencies as well as details on computer hardware for deep learning. It discusses how academics are focusing on anonymity, usability, and error detection regarding cryptocurrencies such as bitcoin. The article also looks at how hardware...
| Publicado en: | Communications of the ACM Vol. 60; no. 5; pp. 48 - 52 |
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| Autores principales: | , |
| Formato: | Artículo |
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Association for Computing Machinery
May2017
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=122701123&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 122701123 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00010782 ACM jtl: Communications of the ACM issn: 00010782 maglogo: N pubinfo: dt: May2017 vid: 60 iid: 5 pid: 68 pub: Association for Computing Machinery artinfo: ui: 122701123 10.1145/3024928 ppf: 48 ppct: 4 formats: tig: atl: Research for Practice: Cryptocurrencies, Blockchains, and Smart Contracts; Hardware for Deep Learning. aug: au: Bailis, Peter Song Han affil: Assistant professor of computer science at Stanford University PhD student at Stanford University, Stanford, CA su: Bitcoin Digital currency User-centered system design Deep learning Computer network software Big data sug: subj: Bitcoin Digital currency User-centered system design Deep learning Computer network software Big data ab: The article provides information on academic research of cryptocurrencies as well as details on computer hardware for deep learning. It discusses how academics are focusing on anonymity, usability, and error detection regarding cryptocurrencies such as bitcoin. The article also looks at how hardware and hardware-aware techniques are used to compress and improve the performance of networks as well as manage energy consumption. pubtype: Periodical doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2017 holdings: @attributes: islocal: N |
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