{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T13:28:54Z","timestamp":1774618134665,"version":"3.50.1"},"reference-count":34,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,5,1]],"date-time":"2020-05-01T00:00:00Z","timestamp":1588291200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,5,1]],"date-time":"2020-05-01T00:00:00Z","timestamp":1588291200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,5,1]],"date-time":"2020-05-01T00:00:00Z","timestamp":1588291200000},"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":[[2020,5]]},"DOI":"10.1109\/icassp40776.2020.9054527","type":"proceedings-article","created":{"date-parts":[[2020,4,9]],"date-time":"2020-04-09T16:21:13Z","timestamp":1586449273000},"page":"2068-2072","source":"Crossref","is-referenced-by-count":9,"title":["Deriving Compact Feature Representations Via Annealed Contraction"],"prefix":"10.1109","author":[{"given":"Muhammad A.","family":"Shah","sequence":"first","affiliation":[]},{"given":"Bhiksha","family":"Raj","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.355"},{"key":"ref32","doi-asserted-by":"crossref","DOI":"10.1609\/aaai.v30i1.10449","article-title":"Face model compression by distilling knowledge from neurons","author":"luo","year":"2016","journal-title":"AAAI"},{"key":"ref31","article-title":"Net2net: Accelerating learning via knowledge transfer","author":"chen","year":"2015","journal-title":"arXiv preprint arXiv 1511 05271"},{"key":"ref30","article-title":"Fitnets: Hints for thin deep nets","author":"romero","year":"2014","journal-title":"arXiv preprint arXiv 1412 6550"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00583"},{"key":"ref10","first-page":"1135","article-title":"Learning both weights and connections for efficient neural network","author":"han","year":"2015","journal-title":"NIPS"},{"key":"ref11","first-page":"662","article-title":"Less is more: Towards compact cnns","author":"zhou","year":"2016","journal-title":"ECCV"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.173"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.280"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.126"},{"key":"ref15","article-title":"Distilling the knowledge in a neural network","author":"hinton","year":"2015","journal-title":"arXiv preprint arXiv 1503 02531"},{"key":"ref16","article-title":"Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer","author":"zagoruyko","year":"2016","journal-title":"arXiv preprint arXiv 1612 03928"},{"key":"ref17","first-page":"0","article-title":"Adversarial network compression","author":"belagiannis","year":"2018","journal-title":"Proceedings of ECCV"},{"key":"ref18","article-title":"Learning multiple layers of features from tiny images","author":"krizhevsky","year":"2009","journal-title":"Tech Rep"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2006.79"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2017.124"},{"key":"ref28","article-title":"The lottery ticket hypothesis: Finding sparse, trainable neural networks","author":"frankle","year":"2018","journal-title":"arXiv preprint arXiv 1803 03635"},{"key":"ref3","first-page":"447","author":"reid","year":"2010","journal-title":"Generalization Bounds"},{"key":"ref27","article-title":"To prune, or not to prune: exploring the efficacy of pruning for model compression","author":"zhu","year":"2017","journal-title":"arXiv preprint arXiv 1710 01878"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1186\/s41074-019-0056-0"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2015.2475625"},{"key":"ref29","first-page":"535","article-title":"Model compression","author":"bucilu?a","year":"2006","journal-title":"Proceedings of the 12th ACM SIGKDD"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46681-1_50"},{"key":"ref7","article-title":"Compressing word embeddings via deep compositional code learning","author":"shu","year":"2017","journal-title":"arXiv preprint arXiv 1711 09020"},{"key":"ref2","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"NIPS"},{"key":"ref9","first-page":"3703","article-title":"Beyond filters: Compact feature map for portable deep model","author":"wang","year":"2017","journal-title":"Proceedings of ICML"},{"key":"ref1","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014","journal-title":"arXiv preprint arXiv 1409 1556"},{"key":"ref20","article-title":"Caltech-256 object category dataset","author":"griffin","year":"2007"},{"key":"ref22","volume":"8","author":"touretzky","year":"1996","journal-title":"NIPS"},{"key":"ref21","first-page":"177","article-title":"Comparing biases for minimal network construction with back-propagation","author":"hanson","year":"1989","journal-title":"NIPS"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.541"},{"key":"ref23","article-title":"Pruning filters for efficient convnets","author":"li","year":"2016","journal-title":"arXiv preprint arXiv 1608 08710"},{"key":"ref26","first-page":"2074","article-title":"Learning structured sparsity in deep neural networks","author":"wen","year":"2016","journal-title":"NIPSS"},{"key":"ref25","first-page":"5113","article-title":"Collaborative channel pruning for deep networks","author":"peng","year":"2019","journal-title":"ICML"}],"event":{"name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","location":"Barcelona, Spain","start":{"date-parts":[[2020,5,4]]},"end":{"date-parts":[[2020,5,8]]}},"container-title":["ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9040208\/9052899\/09054527.pdf?arnumber=9054527","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,29]],"date-time":"2023-09-29T15:29:05Z","timestamp":1696001345000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9054527\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5]]},"references-count":34,"URL":"https:\/\/doi.org\/10.1109\/icassp40776.2020.9054527","relation":{},"subject":[],"published":{"date-parts":[[2020,5]]}}}