{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T19:17:46Z","timestamp":1773170266095,"version":"3.50.1"},"reference-count":20,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,7,9]],"date-time":"2023-07-09T00:00:00Z","timestamp":1688860800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,7,9]],"date-time":"2023-07-09T00:00:00Z","timestamp":1688860800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001321","name":"National Research Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001321","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000028","name":"Semiconductor Research Corporation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000028","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000006","name":"Office of Naval Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000006","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000181","name":"Air Force Office of Scientific Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000181","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,7,9]]},"DOI":"10.1109\/dac56929.2023.10248004","type":"proceedings-article","created":{"date-parts":[[2023,9,15]],"date-time":"2023-09-15T17:31:31Z","timestamp":1694799091000},"page":"1-6","source":"Crossref","is-referenced-by-count":10,"title":["Comprehensive Integration of Hyperdimensional Computing with Deep Learning towards Neuro-Symbolic AI"],"prefix":"10.1109","author":[{"given":"Hyunsei","family":"Lee","sequence":"first","affiliation":[{"name":"Daegu Gyeongbuk Institute of Science and Technology"}]},{"given":"Jiseung","family":"Kim","sequence":"additional","affiliation":[{"name":"Daegu Gyeongbuk Institute of Science and Technology"}]},{"given":"Hanning","family":"Chen","sequence":"additional","affiliation":[{"name":"University of California Irvine"}]},{"given":"Ariela","family":"Zeira","sequence":"additional","affiliation":[{"name":"Intel Labs"}]},{"given":"Narayan","family":"Srinivasa","sequence":"additional","affiliation":[{"name":"Intel Labs"}]},{"given":"Mohsen","family":"Imani","sequence":"additional","affiliation":[{"name":"University of California Irvine"}]},{"given":"Yeseong","family":"Kim","sequence":"additional","affiliation":[{"name":"Daegu Gyeongbuk Institute of Science and Technology"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/MDAT.2017.2740839"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICRC.2017.8123650"},{"key":"ref15","article-title":"Inverted residuals and linear bottlenecks: Mobile networks for classification, detection and segmentation","author":"sandler","year":"2018","journal-title":"CoRR"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN55064.2022.9892622"},{"key":"ref20","article-title":"Binarynet: Training deep neural networks with weights and activations constrained to +1 or -1","author":"courbariaux","year":"2016"},{"key":"ref11","article-title":"Distilling the knowledge in a neural network","author":"hinton","year":"2015"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3526241.3530331"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CLOUD.2019.00076"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cjca.2021.09.004"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ACPR.2015.7486599"},{"key":"ref16","article-title":"Efficientnet: Rethinking model scaling for convolutional neural networks","author":"tan","year":"2019","journal-title":"CoRR"},{"key":"ref19","article-title":"Fitnets: Hints for thin deep nets","author":"romero","year":"2014"},{"key":"ref18","article-title":"Neurosymbolic ai: The 3rd wave","author":"garcez","year":"2020"},{"key":"ref8","article-title":"Neuro-symbolic ai: An emerging class of ai workloads and their characterization","author":"susskind","year":"2021"},{"key":"ref7","article-title":"Cifar-100 (canadian institute for advanced research)","author":"krizhevsky","year":"0"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/s13218-019-00623-z"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/s12559-009-9009-8"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/DAC18074.2021.9586235"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/MICRO50266.2020.00039"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3287624.3287667"}],"event":{"name":"2023 60th ACM\/IEEE Design Automation Conference (DAC)","location":"San Francisco, CA, USA","start":{"date-parts":[[2023,7,9]]},"end":{"date-parts":[[2023,7,13]]}},"container-title":["2023 60th ACM\/IEEE Design Automation Conference (DAC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10247654\/10247655\/10248004.pdf?arnumber=10248004","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,2]],"date-time":"2023-10-02T17:42:10Z","timestamp":1696268530000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10248004\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,9]]},"references-count":20,"URL":"https:\/\/doi.org\/10.1109\/dac56929.2023.10248004","relation":{},"subject":[],"published":{"date-parts":[[2023,7,9]]}}}