{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T05:39:07Z","timestamp":1730266747810,"version":"3.28.0"},"reference-count":20,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,6,30]],"date-time":"2024-06-30T00:00:00Z","timestamp":1719705600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,6,30]],"date-time":"2024-06-30T00:00:00Z","timestamp":1719705600000},"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":[[2024,6,30]]},"DOI":"10.1109\/ijcnn60899.2024.10650402","type":"proceedings-article","created":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T17:35:05Z","timestamp":1725903305000},"page":"1-8","source":"Crossref","is-referenced-by-count":0,"title":["Learning a Sparse Neural Network using IHT"],"prefix":"10.1109","author":[{"given":"Saeed","family":"Damadi","sequence":"first","affiliation":[{"name":"University of Maryland, Baltimore County (UMBC),Department of Mathematics and Statistics,Baltimore,USA"}]},{"given":"Soroush","family":"Zolfaghari","sequence":"additional","affiliation":[{"name":"Isfahan University of Technology,Department of Computer Engineering,Isfahan,Iran"}]},{"given":"Mahdi","family":"Rezaie","sequence":"additional","affiliation":[{"name":"Amirkabir University of Technology,Department of Computer Engineering,Tehran,Iran"}]},{"given":"Jinglai","family":"Shen","sequence":"additional","affiliation":[{"name":"University of Maryland, Baltimore County (UMBC),Department of Mathematics and Statistics,Baltimore,USA"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-37717-4_27"},{"key":"ref2","article-title":"Optimal brain damage","volume":"2","author":"LeCun","year":"1989","journal-title":"Advances in neural information processing systems"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"article-title":"The lottery ticket hypothesis: Finding sparse, trainable neural networks","year":"2018","author":"Frankle","key":"ref4"},{"article-title":"Gradient properties of hard thresholding operator","year":"2022","author":"Damadi","key":"ref5"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN54540.2023.10191596"},{"key":"ref7","first-page":"223","article-title":"Convergence of the mini-batch siht algorithm","volume-title":"Intelligent Systems Conference","author":"Damadi"},{"issue":"1847","key":"ref8","first-page":"536","article-title":"M\u00e9thode g\u00e9n\u00e9rale pour la r\u00e9solution des systemes d\u2019\u00e9quations simultan\u00e9es","volume":"25","author":"Cauchy","year":"1847","journal-title":"Comp. Rend. Sci. Paris"},{"issue":"1","key":"ref9","first-page":"10882","article-title":"Sparsity in deep learning: Pruning and growth for efficient inference and training in neural networks","volume":"22","author":"Hoefler","year":"2021","journal-title":"The Journal of Machine Learning Research"},{"article-title":"Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding","year":"2015","author":"Han","key":"ref10"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.21437\/Eurospeech.1997-708"},{"key":"ref12","article-title":"Autoprune: Automatic network pruning by regularizing auxiliary parameters","volume":"32","author":"Xiao","year":"2019","journal-title":"Advances in neural information processing systems"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00508"},{"key":"ref14","article-title":"Optimal brain surgeon: Extensions and performance comparisons","volume":"6","author":"Hassibi","year":"1993","journal-title":"Advances in neural information processing systems"},{"key":"ref15","first-page":"2498","article-title":"Variational dropout sparsifies deep neural networks","volume-title":"International Conference on Machine Learning","author":"Molchanov"},{"article-title":"The state of sparsity in deep neural networks","year":"2019","author":"Gale","key":"ref16"},{"key":"ref17","article-title":"SparseZoo"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1137\/120869778"},{"article-title":"Pytorch: An imperative style, high-performance deep learning library","year":"2019","author":"Paszke","key":"ref19"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1111\/j.1469-1809.1936.tb02137.x"}],"event":{"name":"2024 International Joint Conference on Neural Networks (IJCNN)","start":{"date-parts":[[2024,6,30]]},"location":"Yokohama, Japan","end":{"date-parts":[[2024,7,5]]}},"container-title":["2024 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10649807\/10649898\/10650402.pdf?arnumber=10650402","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,10]],"date-time":"2024-09-10T06:23:20Z","timestamp":1725949400000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10650402\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6,30]]},"references-count":20,"URL":"https:\/\/doi.org\/10.1109\/ijcnn60899.2024.10650402","relation":{},"subject":[],"published":{"date-parts":[[2024,6,30]]}}}