{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T06:02:04Z","timestamp":1780639324264,"version":"3.54.1"},"reference-count":30,"publisher":"IEEE","license":[{"start":{"date-parts":[[2026,4,20]],"date-time":"2026-04-20T00:00:00Z","timestamp":1776643200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,4,20]],"date-time":"2026-04-20T00:00:00Z","timestamp":1776643200000},"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":[[2026,4,20]]},"DOI":"10.23919\/date69613.2026.11539266","type":"proceedings-article","created":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T19:53:10Z","timestamp":1780602790000},"page":"1-7","source":"Crossref","is-referenced-by-count":0,"title":["Grin: HyperGNN Training Framework for Efficient Edge Inference via Hypergraph Restructuring"],"prefix":"10.23919","author":[{"given":"Chaofang","family":"Ma","sequence":"first","affiliation":[{"name":"The Hong Kong University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lin","family":"Jiang","sequence":"additional","affiliation":[{"name":"Northeastern University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zeyu","family":"Li","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xingyu","family":"Liu","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiang","family":"Xu","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology (GZ)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Zhang","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","article-title":"Semi-supervised classification with graph convolutional networks","author":"Kipf","year":"2016"},{"key":"ref2","article-title":"Inductive representation learning on large graphs","volume":"30","author":"Hamilton","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref3","article-title":"Graph attention networks","author":"Veli\u010dkovi\u0107","year":"2017"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/366"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3605776"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3637528.3671457"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3051495"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401133"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3613964"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-021-04197-2"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2023.107765"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/MICRO61859.2024.00094"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/HPCA61900.2025.00073"},{"key":"ref15","article-title":"Graph data augmentation for graph machine learning: A survey","author":"Zhao","year":"2022"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/tkde.2025.3622600"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/3732282"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33013558"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/353"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3182052"},{"key":"ref21","first-page":"19 010","article-title":"Metropolis-hastings data augmentation for graph neural networks","volume":"34","author":"Park","year":"2021","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TAI.2021.3133818"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i12.17315"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.52202\/068431-0139"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2022\/267"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2024.3380643"},{"key":"ref27","article-title":"Variational graph auto-encoders","author":"Kipf","year":"2016"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/HPCA53966.2022.00041"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i7.20726"},{"key":"ref30","first-page":"387","article-title":"Hypergef: A framework enabling efficient fusion for hypergraph neural network on gpus","volume-title":"Proceedings of Machine Learning and Systems","volume":"5","author":"Yu"}],"event":{"name":"2026 Design, Automation &amp; Test in Europe Conference (DATE)","location":"Verona, Italy","start":{"date-parts":[[2026,4,20]]},"end":{"date-parts":[[2026,4,22]]}},"container-title":["2026 Design, Automation &amp;amp; Test in Europe Conference (DATE)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11539023\/11539024\/11539266.pdf?arnumber=11539266","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T05:15:22Z","timestamp":1780636522000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11539266\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,20]]},"references-count":30,"URL":"https:\/\/doi.org\/10.23919\/date69613.2026.11539266","relation":{},"subject":[],"published":{"date-parts":[[2026,4,20]]}}}