{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,7]],"date-time":"2026-01-07T18:41:27Z","timestamp":1767811287595,"version":"3.49.0"},"publisher-location":"New York, NY, USA","reference-count":16,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,1,16]],"date-time":"2023-01-16T00:00:00Z","timestamp":1673827200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,1,16]]},"DOI":"10.1145\/3566097.3568357","type":"proceedings-article","created":{"date-parts":[[2023,1,31]],"date-time":"2023-01-31T18:40:49Z","timestamp":1675190449000},"page":"612-617","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Toward Fair and Efficient Hyperdimensional Computing"],"prefix":"10.1145","author":[{"given":"Yi","family":"Sheng","sequence":"first","affiliation":[{"name":"George Mason University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junhuan","family":"Yang","sequence":"additional","affiliation":[{"name":"George Mason University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weiwen","family":"Jiang","sequence":"additional","affiliation":[{"name":"George Mason University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lei","family":"Yang","sequence":"additional","affiliation":[{"name":"George Mason University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2023,1,31]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"The larger the fairer? small neural networks can achieve fairness for edge devices,\" arXiv preprint arXiv:2202.11317","author":"Sheng Y.","year":"2022","unstructured":"Y. Sheng, J. Yang, Y. Wu, K. Mao, Y. Shi, J. Hu, W. Jiang, and L. Yang, \"The larger the fairer? small neural networks can achieve fairness for edge devices,\" arXiv preprint arXiv:2202.11317, 2022."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/MCAS.2020.2988388"},{"key":"e_1_3_2_1_3_1","volume-title":"Enhdc: Ensemble learning for brain-inspired hyperdimensional computing,\" arXiv preprint arXiv:2203.13542","author":"Wang R.","year":"2022","unstructured":"R. Wang, D. Ma, and X. Jiao, \"Enhdc: Ensemble learning for brain-inspired hyperdimensional computing,\" arXiv preprint arXiv:2203.13542, 2022."},{"key":"e_1_3_2_1_4_1","first-page":"1","volume-title":"Comphd: Efficient hyperdimensional computing using model compression,\" in 2019 IEEE\/ACM International Symposium on Low Power Electronics and Design (ISLPED)","author":"Morris J.","year":"2019","unstructured":"J. Morris, M. Imani, S. Bosch, A. Thomas, H. Shu, and T. Rosing, \"Comphd: Efficient hyperdimensional computing using model compression,\" in 2019 IEEE\/ACM International Symposium on Low Power Electronics and Design (ISLPED), pp. 1--6, 2019."},{"key":"e_1_3_2_1_5_1","first-page":"1","volume-title":"Hierarchical hyperdimensional computing for energy efficient classification,\" in 2018 55th ACM\/ESDA\/IEEE Design Automation Conference (DAC)","author":"Imani M.","year":"2018","unstructured":"M. Imani, C. Huang, D. Kong, and T. Rosing, \"Hierarchical hyperdimensional computing for energy efficient classification,\" in 2018 55th ACM\/ESDA\/IEEE Design Automation Conference (DAC), pp. 1--6, 2018."},{"key":"e_1_3_2_1_6_1","first-page":"1","volume-title":"Hierarchical hyperdimensional computing for energy efficient classification,\" in 2018 55th ACM\/ESDA\/IEEE Design Automation Conference (DAC)","author":"Imani M.","year":"2018","unstructured":"M. Imani, C. Huang, D. Kong, and T. Rosing, \"Hierarchical hyperdimensional computing for energy efficient classification,\" in 2018 55th ACM\/ESDA\/IEEE Design Automation Conference (DAC), pp. 1--6, IEEE, 2018."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3316781.3317757"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2012.2211477"},{"key":"e_1_3_2_1_9_1","volume-title":"Fitzpatrick skin typing: Applications in dermatology,\" Indian journal of dermatology, venereology and leprology","author":"Sachdeva S.","unstructured":"S. Sachdeva et al., \"Fitzpatrick skin typing: Applications in dermatology,\" Indian journal of dermatology, venereology and leprology, vol. 75, no. 1, p. 93, 2009."},{"key":"e_1_3_2_1_10_1","first-page":"85","volume-title":"Co-exploring neural architecture and network-on-chip design for real-time artificial intelligence,\" in 2020 25th Asia and South Pacific Design Automation Conference (ASP-DAC)","author":"Yang L.","year":"2020","unstructured":"L. Yang, W. Jiang, W. Liu, H. Edwin, Y. Shi, and J. Hu, \"Co-exploring neural architecture and network-on-chip design for real-time artificial intelligence,\" in 2020 25th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 85--90, IEEE, 2020."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2020.2986127"},{"issue":"3","key":"e_1_3_2_1_12_1","first-page":"4","article-title":"Simple statistical gradient-following algorithms for connectionist reinforcement learning","volume":"8","author":"Williams R. J.","year":"1992","unstructured":"R. J. Williams, \"Simple statistical gradient-following algorithms for connectionist reinforcement learning,\" Machine learning, vol. 8, no. 3--4, pp. 229--256, 1992.","journal-title":"Machine learning"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.1986.4767851"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"crossref","unstructured":"C.-X. Deng G.-B. Wang and X.-R. Yang \"Image edge detection algorithm based on improved canny operator \" in 2013 International Conference on Wavelet Analysis and Pattern Recognition pp. 168--172 2013.","DOI":"10.1109\/ICWAPR.2013.6599311"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2015.02.024"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3003890"}],"event":{"name":"ASPDAC '23: 28th Asia and South Pacific Design Automation Conference","location":"Tokyo Japan","acronym":"ASPDAC '23","sponsor":["SIGDA ACM Special Interest Group on Design Automation","IEEE CEDA","IEICE","IEEE CAS","IPSJ"]},"container-title":["Proceedings of the 28th Asia and South Pacific Design Automation Conference"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3566097.3568357","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3566097.3568357","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,7]],"date-time":"2026-01-07T17:35:24Z","timestamp":1767807324000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3566097.3568357"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,16]]},"references-count":16,"alternative-id":["10.1145\/3566097.3568357","10.1145\/3566097"],"URL":"https:\/\/doi.org\/10.1145\/3566097.3568357","relation":{},"subject":[],"published":{"date-parts":[[2023,1,16]]},"assertion":[{"value":"2023-01-31","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}