{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T11:36:13Z","timestamp":1780486573247,"version":"3.54.1"},"reference-count":35,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,4,6]],"date-time":"2025-04-06T00:00:00Z","timestamp":1743897600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,4,6]],"date-time":"2025-04-06T00:00:00Z","timestamp":1743897600000},"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":[[2025,4,6]]},"DOI":"10.1109\/icassp49660.2025.10888970","type":"proceedings-article","created":{"date-parts":[[2025,3,12]],"date-time":"2025-03-12T17:15:19Z","timestamp":1741799719000},"page":"1-5","source":"Crossref","is-referenced-by-count":2,"title":["Generative Dataset Distillation Based on Self-knowledge Distillation"],"prefix":"10.1109","author":[{"given":"Longzhen","family":"Li","sequence":"first","affiliation":[{"name":"Hokkaido University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guang","family":"Li","sequence":"additional","affiliation":[{"name":"Hokkaido University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ren","family":"Togo","sequence":"additional","affiliation":[{"name":"Hokkaido University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Keisuke","family":"Maeda","sequence":"additional","affiliation":[{"name":"Hokkaido University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takahiro","family":"Ogawa","sequence":"additional","affiliation":[{"name":"Hokkaido University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Miki","family":"Haseyama","sequence":"additional","affiliation":[{"name":"Hokkaido University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/s11831-019-09344-w"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-021-00444-8"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1111\/2041-210X.13256"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-017-0110-7"},{"key":"ref5","article-title":"Dataset distillation","author":"Wang","year":"2018"},{"key":"ref6","article-title":"Awesome dataset distillation","author":"Li","year":"2022"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP40778.2020.9191357"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2022.107189"},{"key":"ref9","first-page":"1","article-title":"Dataset distillation for medical dataset sharing","volume-title":"Proc. AAAI Workshop","author":"Li"},{"key":"ref10","first-page":"1","article-title":"An efficient dataset condensation plugin and its application to continual learning","volume-title":"Proc. NeurIPS","author":"Yang"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN54540.2023.10191879"},{"key":"ref12","first-page":"9206","article-title":"Generative teaching networks: Accelerating neural architecture search by learning to generate synthetic training data","volume-title":"Proc. ICML","author":"Such"},{"key":"ref13","first-page":"1","article-title":"Dataset condensation with gradient matching","volume-title":"Proc. ICLR","author":"Zhao"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01045"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2024.106154"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-93806-1_4"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW63382.2024.00762"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-93806-1_7"},{"key":"ref19","first-page":"1","article-title":"Generative adversarial nets","volume-title":"Proc. NeurIPS","author":"Goodfellow"},{"key":"ref20","first-page":"109","article-title":"Super-samples from kernel herding","volume-title":"Proc. UAI","author":"Chen"},{"key":"ref21","first-page":"1","article-title":"Fair clustering through fairlets","volume-title":"Proc. NeurIPS","author":"Chierichetti"},{"key":"ref22","first-page":"1","article-title":"An empirical study of example forgetting during deep neural network learning","volume-title":"Proc. ICLR","author":"Toneva"},{"key":"ref23","first-page":"12674","article-title":"Dataset condensation with differentiable siamese augmentation","volume-title":"Proc. ICML","author":"Zhao"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/WACV56688.2023.00645"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01188"},{"key":"ref26","first-page":"5186","article-title":"Dataset distillation with infinitely wide convolutional networks","volume-title":"Proc. NeurIPS","author":"Nguyen"},{"key":"ref27","first-page":"1","article-title":"Dataset distillation using neural feature regression","volume-title":"Proc. NeurIPS","author":"Zhou"},{"key":"ref28","article-title":"Conditional generative adversarial nets","author":"Mirza","year":"2014"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref30","article-title":"Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms","author":"Xiao","year":"2017"},{"key":"ref31","author":"Krizhevsky","year":"2009","journal-title":"Learning multiple layers of features from tiny images"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00459"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref34","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","volume-title":"Proc. NeurIPS","author":"Krizhevsky"},{"key":"ref35","first-page":"1","article-title":"Very deep convolutional networks for large-scale image recognition","volume-title":"Proc. ICLR","author":"Simonyan"}],"event":{"name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","location":"Hyderabad, India","start":{"date-parts":[[2025,4,6]]},"end":{"date-parts":[[2025,4,11]]}},"container-title":["ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10887540\/10887541\/10888970.pdf?arnumber=10888970","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T05:23:37Z","timestamp":1774416217000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10888970\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,6]]},"references-count":35,"URL":"https:\/\/doi.org\/10.1109\/icassp49660.2025.10888970","relation":{},"subject":[],"published":{"date-parts":[[2025,4,6]]}}}