Talk:Deep learning
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Energy consumption
I am considering adding information regarding power consumption. Currently I see two directions: low-power inference for embedded devices[1] and low-power training for huge networks[2]. Please let me know if you know of more credible and/or overview sources discussing the concerns. p.s. This may be a discussion for another page, e.g. ML or ANNs. Cheater no1 (talk) 13:16, 13 November 2020 (UTC)
Planned slow motion cleanup of reference spamming and overciting
I plan to attempt a slow motion cleanup of reference spamming. The typical case is an obscure non-notable paper where it does a poor job of supporting the items which cited it, particularly where the material is still cited without it. When all of the references looked equally good/applicable on overcited items, I left them all in. Sincerely, North8000 (talk) 16:29, 7 March 2022 (UTC)
- Completed through the first image and lead. North8000 (talk) 20:20, 7 March 2022 (UTC)
- Completed through the first 5 paragraphs of the overview section. North8000 (talk) 22:43, 7 March 2022 (UTC)
- Completed through end of overview section. North8000 (talk) 02:54, 8 March 2022 (UTC)
- Complete through interpretation section. That section still has some over-cited items, but the remaining ones all look useful. North8000 (talk) 17:56, 14 March 2022 (UTC)
- Complete through 1st 13 paragraphs of history section.North8000 (talk) 18:16, 14 March 2022 (UTC)
- Complete through history section including revolution subsection.North8000 (talk) 21:04, 15 March 2022 (UTC)
- Complete through the Neural Networks section including all subsections. North8000 (talk) 14:23, 17 March 2022 (UTC)
- Complete through hardware section. North8000 (talk) 00:07, 18 March 2022 (UTC)
- Completed the articleNorth8000 (talk) 02:54, 18 March 2022 (UTC)
References
References
- ^ Gauen, Kent; Rangan, Rohit; Mohan, Anup; Lu, Yung-Hsiang; Liu, Wei; Berg, Alexander C. (2017-01). "Low-power image recognition challenge". 2017 22nd Asia and South Pacific Design Automation Conference (ASP-DAC). Chiba: IEEE: 99–104. doi:10.1109/ASPDAC.2017.7858303. ISBN 978-1-5090-1558-0.
{{cite journal}}: Check date values in:|date=(help)CS1 maint: periodical has ISBN (link) - ^ "Estimation of energy consumption in machine learning". Journal of Parallel and Distributed Computing. 134: 75–88. 2019-12-01. doi:10.1016/j.jpdc.2019.07.007. ISSN 0743-7315.
Wiki Education assignment: Research Process and Methodology - FA23 - Sect 202 - Thu
This article was the subject of a Wiki Education Foundation-supported course assignment, between 6 September 2023 and 14 December 2023. Further details are available on the course page. Student editor(s): HELLOEXTRACREDIT (article contribs).
— Assignment last updated by HELLOEXTRACREDIT (talk) 04:30, 26 November 2023 (UTC)
Reply to User:WeyerStudentOfAgrippa
This is a reply to the question posed by you here. I reverted the edit by the IP because the range 194.247.67.196/30 (talk · contribs · IP contribs · WHOIS) quite clearly inaproppriately promoted the article by Murray et. al., e.g. [1], [2]. This leads me to think it is a spam campaign, so I reverted all edits citing this article (all of them were from this range). Janhrach (talk) 12:11, 5 October 2024 (UTC)
- @Janhrach Thanks for responding. It's a primary source showing the existence of an application, but it's not necessarily a notable application without secondary sourcing.WeyerStudentOfAgrippa (talk) 12:24, 5 October 2024 (UTC)
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