{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,7]],"date-time":"2024-09-07T11:07:24Z","timestamp":1725707244518},"reference-count":28,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,7,1]],"date-time":"2020-07-01T00:00:00Z","timestamp":1593561600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,7,1]],"date-time":"2020-07-01T00:00:00Z","timestamp":1593561600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,7,1]],"date-time":"2020-07-01T00:00:00Z","timestamp":1593561600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,7]]},"DOI":"10.1109\/dac18072.2020.9218501","type":"proceedings-article","created":{"date-parts":[[2020,10,9]],"date-time":"2020-10-09T19:57:03Z","timestamp":1602273423000},"page":"1-6","source":"Crossref","is-referenced-by-count":3,"title":["ALF: Autoencoder-based Low-rank Filter-sharing for Efficient Convolutional Neural Networks"],"prefix":"10.1109","author":[{"given":"Alexander","family":"Frickenstein","sequence":"first","affiliation":[]},{"given":"Manoj-Rohit","family":"Vemparala","sequence":"additional","affiliation":[]},{"given":"Nael","family":"Fasfous","sequence":"additional","affiliation":[]},{"given":"Laura","family":"Hauenschild","sequence":"additional","affiliation":[]},{"given":"Naveen-Shankar","family":"Nagaraja","sequence":"additional","affiliation":[]},{"given":"Christian","family":"Unger","sequence":"additional","affiliation":[]},{"given":"Walter","family":"Stechele","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA40945.2020.9197119"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"article-title":"Learning both weights and connections for efficient neural networks","volume-title":"NeurIPS","author":"Han","key":"ref3"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2018.00083"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CRV.2019.00011"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3240765.3240803"},{"article-title":"Binarized Neural Networks","volume-title":"NeurIPS","author":"Hubara","key":"ref8"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.23919\/DATE48585.2020.9116308"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2502579"},{"article-title":"Low-rank tucker decomposition of large tensors using tensorsketch","volume-title":"NeurIPS","author":"Malik","key":"ref11"},{"article-title":"DSC: Dense-sparse convolution for vectorized inference of cnns","volume-title":"CVPR-W","author":"Frickenstein","key":"ref12"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00447"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_48"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00293"},{"article-title":"ProxylessNAS: Direct neural architecture search on target task and hardware","volume-title":"ICLR","author":"Cai","key":"ref16"},{"article-title":"Dynamic network surgery for efficient DNNs","volume-title":"NeurIPS","author":"Guo","key":"ref17"},{"article-title":"Structadmm: A systematic, high-efficiency framework of structured weight pruning for dnns","year":"2018","author":"Zhang","key":"ref18"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.98"},{"article-title":"SqueezeNet: AlexNet-level accuracy with 50\u00d7 fewer parameters and <0.5MB model size","year":"2016","author":"Iandola","key":"ref20"},{"article-title":"Contrastive Representation Distillation","volume-title":"ICLR","author":"Tian","key":"ref21"},{"author":"Krizhevsky","key":"ref22","article-title":"Cifar-10 (canadian institute for advanced research)"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"article-title":"Understanding the difficulty of training deep feedforward neural networks","volume-title":"PMLR","author":"Glorot","key":"ref25"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ISPASS.2019.00042"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/3007787.3001177"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/MICRO.2016.7783725"}],"event":{"name":"2020 57th ACM\/IEEE Design Automation Conference (DAC)","start":{"date-parts":[[2020,7,20]]},"location":"San Francisco, CA, USA","end":{"date-parts":[[2020,7,24]]}},"container-title":["2020 57th ACM\/IEEE Design Automation Conference (DAC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9211868\/9218488\/09218501.pdf?arnumber=9218501","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,24]],"date-time":"2024-01-24T00:53:46Z","timestamp":1706057626000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9218501\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,7]]},"references-count":28,"URL":"https:\/\/doi.org\/10.1109\/dac18072.2020.9218501","relation":{},"subject":[],"published":{"date-parts":[[2020,7]]}}}