{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T06:17:52Z","timestamp":1783059472637,"version":"3.54.6"},"reference-count":23,"publisher":"IEEE","license":[{"start":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T00:00:00Z","timestamp":1773619200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T00:00:00Z","timestamp":1773619200000},"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":[[2026,3,16]]},"DOI":"10.1109\/percomworkshops68308.2026.11585488","type":"proceedings-article","created":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T19:42:40Z","timestamp":1783021360000},"page":"1-6","source":"Crossref","is-referenced-by-count":0,"title":["Compression Techniques for Membership Functions to Fuzzy Sets Learned from Data"],"prefix":"10.1109","author":[{"given":"Amirreza Dashti","family":"Genave","sequence":"first","affiliation":[{"name":"University of Milan,Department of Computer Science,Milano,Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dario","family":"Malchiodi","sequence":"additional","affiliation":[{"name":"University of Milan,Department of Computer Science,Milano,Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marco","family":"Frasca","sequence":"additional","affiliation":[{"name":"University of Milan,Department of Computer Science,Milano,Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-03200-9_6"},{"key":"ref2","first-page":"598","article-title":"Optimal brain damage","volume":"2","author":"LeCun","year":"1990","journal-title":"Advances in Neural Information Processing Systems (NeurIPS)"},{"key":"ref3","volume-title":"Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding","author":"Han","year":"2016"},{"key":"ref4","article-title":"Compressing deep convolutional networks using vector quantization","volume-title":"International Conference on Learning Representations (ICLR)","author":"Gong"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2022.11.072"},{"key":"ref6","first-page":"129","article-title":"What is the state of neural network pruning?","volume-title":"Proceedings of Machine Learning and Systems","volume":"2","author":"Blalock"},{"key":"ref7","volume-title":"A survey of quantization methods for efficient neural network inference","author":"Gholami","year":"2021"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972719.13"},{"key":"ref9","volume-title":"Compressed support vector machines","author":"Xu","year":"2015"},{"key":"ref10","first-page":"110257","article-title":"Pruning redundant and noisy support vectors for least squares support vector machines","volume":"263","author":"Xia","year":"2023","journal-title":"Knowledge-Based Systems"},{"key":"ref11","doi-asserted-by":"crossref","first-page":"2233","DOI":"10.1007\/s00521-021-06526-1","article-title":"Compact support vector machine models through support vector reduction","volume":"34","author":"Chen","year":"2022","journal-title":"Neural Computing and Applications"},{"key":"ref12","volume-title":"Training with reduced precision of a support vector machine model for text classification","author":"\u017burek","year":"2020"},{"key":"ref13","first-page":"1177","article-title":"Random features for large-scale kernel machines","volume":"20","author":"Rahimi","year":"2007","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1023\/B:MACH.0000008084.60811.49"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.1993.713929"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/JSTSP.2020.2975903"},{"key":"ref17","article-title":"Analysis of Compression Techniques for Membership Functions to Fuzzy Sets Learned from Data","volume-title":"Master\u2019s thesis","author":"Genave","year":"2025"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3167132.3167345"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-12544-8_2"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00286"},{"key":"ref21","first-page":"682","article-title":"Using the nystr\u00f6m method to speed up kernel machines","volume":"13","author":"Williams","year":"2001","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/S1389-0417(01)00057-2"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.na.2010.06.035"}],"event":{"name":"2026 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)","location":"Pisa, Italy","start":{"date-parts":[[2026,3,16]]},"end":{"date-parts":[[2026,3,20]]}},"container-title":["2026 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11585185\/11585186\/11585488.pdf?arnumber=11585488","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T05:27:24Z","timestamp":1783056444000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11585488\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,16]]},"references-count":23,"URL":"https:\/\/doi.org\/10.1109\/percomworkshops68308.2026.11585488","relation":{},"subject":[],"published":{"date-parts":[[2026,3,16]]}}}