{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T03:02:14Z","timestamp":1730343734385,"version":"3.28.0"},"reference-count":28,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,8,23]],"date-time":"2021-08-23T00:00:00Z","timestamp":1629676800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,8,23]],"date-time":"2021-08-23T00:00:00Z","timestamp":1629676800000},"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":[[2021,8,23]]},"DOI":"10.23919\/eusipco54536.2021.9616015","type":"proceedings-article","created":{"date-parts":[[2021,12,8]],"date-time":"2021-12-08T21:55:53Z","timestamp":1639000553000},"page":"1446-1450","source":"Crossref","is-referenced-by-count":0,"title":["Classification Error Approximation of a Compressed Linear Softmax Layer"],"prefix":"10.23919","author":[{"given":"Diana","family":"Resmerita","sequence":"first","affiliation":[]},{"given":"Rodrigo Cabral","family":"Farias","sequence":"additional","affiliation":[]},{"given":"Lionel","family":"Fillatre","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","article-title":"Quantizing deep convolutional networks for efficient inference: A whitepaper","volume":"abs 1806 8342","author":"krishnamoorthi","year":"2018","journal-title":"CoRR"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00286"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1631\/FITEE.1700789"},{"key":"ref13","article-title":"Deep compression: Compressing deep neural network with pruning, trained quantization and huffman coding","author":"han","year":"2016","journal-title":"4th ICLR"},{"key":"ref14","first-page":"254","article-title":"Stronger generalization bounds for deep nets via a compression approach","author":"arora","year":"2018","journal-title":"International Conference on Machine Learning"},{"journal-title":"Elements of Information Theory","year":"2006","author":"cover","key":"ref15"},{"key":"ref16","first-page":"2102","article-title":"Rate distortion for model compression: From theory to practice","author":"gao","year":"2019","journal-title":"International Conference on Machine Learning"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/72.363478"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/0893-6080(88)90023-8"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01170"},{"key":"ref4","article-title":"Exploring the regularity of sparse structure in convolutional neural networks","author":"mao","year":"2017","journal-title":"CoRR"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/377939.377946"},{"key":"ref3","article-title":"Mobilenets: Efficient convolutional neural networks for mobile vision applications","author":"howard","year":"2017","journal-title":"CoRR"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/SSP49050.2021.9513733"},{"key":"ref6","article-title":"Compressing deep convolutional networks using vector quantization","author":"gong","year":"2014","journal-title":"CoRR"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3005348"},{"key":"ref8","first-page":"4107","article-title":"Binarized neural networks","author":"hubara","year":"2016","journal-title":"NIPS"},{"journal-title":"Ristretto Hardware-Oriented Approximation of Convolutional Neural Networks","year":"2016","author":"gysel","key":"ref7"},{"journal-title":"Squeezenet Alexnet-level accuracy with 50x fewer parameters and! 1mb model size","year":"2016","author":"iandola","key":"ref2"},{"key":"ref9","first-page":"525","article-title":"Xnor-net: ImageNet classification using binary convolutional neural networks","author":"rastegari","year":"2016","journal-title":"Computer Vision - ECCV"},{"journal-title":"Deep Learning","year":"2016","author":"goodfellow","key":"ref1"},{"key":"ref20","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2015","journal-title":"The 3rd ICLR"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT.2016.7541669"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-2341-0"},{"key":"ref23","article-title":"Compression des r&#x00E9;seaux de neurones profonds &#x00E0; base de quantification uniforme et non-uniforme","author":"resmerita","year":"2019","journal-title":"Colloque GRETSI"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.2307\/1403446"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-05261-3"}],"event":{"name":"2021 29th European Signal Processing Conference (EUSIPCO)","start":{"date-parts":[[2021,8,23]]},"location":"Dublin, Ireland","end":{"date-parts":[[2021,8,27]]}},"container-title":["2021 29th European Signal Processing Conference (EUSIPCO)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9615915\/9615917\/09616015.pdf?arnumber=9616015","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,3,21]],"date-time":"2022-03-21T20:57:27Z","timestamp":1647896247000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9616015\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,23]]},"references-count":28,"URL":"https:\/\/doi.org\/10.23919\/eusipco54536.2021.9616015","relation":{},"subject":[],"published":{"date-parts":[[2021,8,23]]}}}