{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,8]],"date-time":"2024-09-08T04:50:32Z","timestamp":1725771032606},"reference-count":30,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,10,16]],"date-time":"2022-10-16T00:00:00Z","timestamp":1665878400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,10,16]],"date-time":"2022-10-16T00:00:00Z","timestamp":1665878400000},"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":[[2022,10,16]]},"DOI":"10.1109\/icip46576.2022.9897718","type":"proceedings-article","created":{"date-parts":[[2022,11,3]],"date-time":"2022-11-03T21:27:24Z","timestamp":1667510844000},"page":"931-935","source":"Crossref","is-referenced-by-count":2,"title":["Extracting Effective Subnetworks with Gumbel-Softmax"],"prefix":"10.1109","author":[{"given":"Robin","family":"Dupont","sequence":"first","affiliation":[{"name":"Sorbonne Universit&#x00E9;,LIP6,Paris"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammed","family":"Amine Alaoui","sequence":"additional","affiliation":[{"name":"Netatmo,Boulogne-Billancourt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hichem","family":"Sahbi","sequence":"additional","affiliation":[{"name":"Sorbonne Universit&#x00E9;,LIP6,Paris"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alice","family":"Lebois","sequence":"additional","affiliation":[{"name":"Netatmo,Boulogne-Billancourt"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00291"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref3","article-title":"Mobilenets: Efficient convolutional neural networks for mobile vision applications","author":"Howard","year":"2017","journal-title":"CoRR"},{"article-title":"Efficientnet: Rethinking model scaling for convolutional neural networks","volume-title":"ICML. 2019, vol. 97 of Proceedings of Machine Learning Research","author":"Tan","key":"ref4"},{"key":"ref5","article-title":"Distilling the knowledge in a neural network","author":"Hinton","year":"2015","journal-title":"CoRR"},{"article-title":"Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer","volume-title":"ICLR","author":"Zagoruyko","key":"ref6"},{"article-title":"Fitnets: Hints for thin deep nets","volume-title":"ICLR","author":"Romero","key":"ref7"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5963"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00454"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00938"},{"article-title":"Optimal brain damage","volume-title":"NIPS","author":"LeCun","key":"ref11"},{"article-title":"Second order derivatives for network pruning: Optimal brain surgeon","volume-title":"NIPS","author":"Hassibi","key":"ref12"},{"article-title":"Learning both weights and connections for efficient neural network","volume-title":"NIPS","author":"Han","key":"ref13"},{"article-title":"Pruning filters for efficient convnets","volume-title":"ICLR","author":"Li","key":"ref14"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.298"},{"article-title":"Deep compression: Compressing deep neural network with pruning, trained quantization and huffman coding","volume-title":"ICLR","author":"Han","key":"ref16"},{"article-title":"The lottery ticket hypothesis: Finding sparse, trainable neural networks","volume-title":"ICLR","author":"Frankle","key":"ref17"},{"article-title":"Rethinking the value of network pruning","volume-title":"ICLR","author":"Liu","key":"ref18"},{"article-title":"Snip: single-shot network pruning based on connection sensitivity","volume-title":"ICLR","author":"Lee","key":"ref19"},{"article-title":"Picking winning tickets before training by preserving gradient flow","volume-title":"ICLR","author":"Wang","key":"ref20"},{"article-title":"Pruning neural networks without any data by iteratively conserving synaptic flow","volume-title":"NeurIPS","author":"Tanaka","key":"ref21"},{"article-title":"Proving the lottery ticket hypothesis: Pruning is all you need","volume-title":"ICML","author":"Malach","key":"ref22"},{"article-title":"Optimal lottery tickets via subset sum: Logarithmic over-parameterization is sufficient","volume-title":"NeurIPS 2020","author":"Pensia","key":"ref23"},{"article-title":"Logarithmic pruning is all you need","volume-title":"NeurIPS 2020","author":"Orseau","key":"ref24"},{"article-title":"Deconstructing lottery tickets: Zeros, signs, and the supermask","volume-title":"NeurIPS","author":"Zhou","key":"ref25"},{"key":"ref26","article-title":"Estimating or propagating gradients through stochastic neurons for conditional computation","author":"Bengio","year":"2013","journal-title":"CoRR"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01191"},{"article-title":"Categorical reparameterization with gumbel-softmax","volume-title":"ICLR","author":"Jang","key":"ref28"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"article-title":"ASLP - Our implementation","year":"2022","author":"Dupont","key":"ref30"}],"event":{"name":"2022 IEEE International Conference on Image Processing (ICIP)","start":{"date-parts":[[2022,10,16]]},"location":"Bordeaux, France","end":{"date-parts":[[2022,10,19]]}},"container-title":["2022 IEEE International Conference on Image Processing (ICIP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9897158\/9897159\/09897718.pdf?arnumber=9897718","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T21:38:54Z","timestamp":1705959534000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9897718\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,16]]},"references-count":30,"URL":"https:\/\/doi.org\/10.1109\/icip46576.2022.9897718","relation":{},"subject":[],"published":{"date-parts":[[2022,10,16]]}}}