{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T05:26:55Z","timestamp":1730266015458,"version":"3.28.0"},"reference-count":38,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,7,18]],"date-time":"2021-07-18T00:00:00Z","timestamp":1626566400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,7,18]],"date-time":"2021-07-18T00:00:00Z","timestamp":1626566400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,7,18]],"date-time":"2021-07-18T00:00:00Z","timestamp":1626566400000},"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":[[2021,7,18]]},"DOI":"10.1109\/ijcnn52387.2021.9533411","type":"proceedings-article","created":{"date-parts":[[2021,9,20]],"date-time":"2021-09-20T21:27:41Z","timestamp":1632173261000},"page":"1-8","source":"Crossref","is-referenced-by-count":3,"title":["Topological Gradient-based Competitive Learning"],"prefix":"10.1109","author":[{"given":"Pietro","family":"Barbiero","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gabriele","family":"Ciravegna","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vincenzo","family":"Randazzo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eros","family":"Pasero","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Giansalvo","family":"Cirrincione","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref38","first-page":"2825","article-title":"Scikit-learn: Machine learning in python","volume":"12","author":"pedregosa","year":"2011","journal-title":"The Journal of Machine Learning Research"},{"doi-asserted-by":"publisher","key":"ref33","DOI":"10.1207\/s15516709cog0901_5"},{"doi-asserted-by":"publisher","key":"ref32","DOI":"10.1109\/ACCESS.2020.2999155"},{"key":"ref31","article-title":"Learning-regulated context relevant topographical map","volume":"26","author":"hartono","year":"2014","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"doi-asserted-by":"publisher","key":"ref30","DOI":"10.1109\/ICCV.2017.626"},{"key":"ref37","first-page":"265","article-title":"Tensorflow: A system for large-scale machine learning","author":"abadi","year":"0","journal-title":"12th USENIX Symposium on Operating Systems Design and Implementation ( OSDI 16)"},{"key":"ref36","article-title":"Design of experiments of the nips 2003 variable selection benchmark","volume":"253","author":"guyon","year":"0","journal-title":"NIPS 2003 Workshop on Feature Extraction and Feature Selection"},{"year":"2007","author":"haykin","journal-title":"Neural Networks A Comprehensive Foundation","key":"ref35"},{"doi-asserted-by":"publisher","key":"ref34","DOI":"10.1162\/neco.1989.1.3.295"},{"key":"ref10","first-page":"625","article-title":"A growing neural gas network learns topologies","author":"fritzke","year":"1995","journal-title":"Advances in neural information processing systems"},{"doi-asserted-by":"publisher","key":"ref11","DOI":"10.1007\/BFb0020222"},{"doi-asserted-by":"publisher","key":"ref12","DOI":"10.1109\/TNNLS.2016.2570124"},{"doi-asserted-by":"publisher","key":"ref13","DOI":"10.1109\/IJCNN.2018.8489545"},{"doi-asserted-by":"publisher","key":"ref14","DOI":"10.4324\/9781410612403"},{"doi-asserted-by":"publisher","key":"ref15","DOI":"10.1007\/978-1-4471-2063-6_104"},{"doi-asserted-by":"publisher","key":"ref16","DOI":"10.1109\/IJCNN.1991.155554"},{"doi-asserted-by":"publisher","key":"ref17","DOI":"10.1016\/0893-6080(94)90109-0"},{"key":"ref18","article-title":"Some competitive learning methods","author":"fritzkc","year":"1997","journal-title":"Artificial Intelligence Institute Dresden University of Technology"},{"year":"2020","author":"barbiero","journal-title":"Modeling generalization in machine learning A methodological and computational study","key":"ref19"},{"key":"ref28","article-title":"Learning discrete representations via information maximizing self-augmented training","author":"hu","year":"2017","journal-title":"ArXiv Preprint"},{"doi-asserted-by":"publisher","key":"ref4","DOI":"10.1093\/comjnl\/16.1.30"},{"doi-asserted-by":"publisher","key":"ref27","DOI":"10.1109\/TMM.2017.2745702"},{"key":"ref3","first-page":"226","article-title":"A density-based algorithm for discovering clusters in large spatial databases with noise","volume":"96","author":"ester","year":"1996","journal-title":"KDD"},{"key":"ref6","volume":"344","author":"kaufman","year":"2009","journal-title":"Finding Groups in Data An Introduction to Cluster Analysis"},{"doi-asserted-by":"publisher","key":"ref29","DOI":"10.1109\/CVPR.2016.556"},{"doi-asserted-by":"publisher","key":"ref5","DOI":"10.1093\/comjnl\/20.4.364"},{"doi-asserted-by":"publisher","key":"ref8","DOI":"10.1007\/BF00337288"},{"doi-asserted-by":"publisher","key":"ref7","DOI":"10.1016\/j.neunet.2019.07.018"},{"key":"ref2","volume":"38","author":"mclachlan","year":"1988","journal-title":"Mixture Models Inference and Applications to Clustering"},{"year":"1991","author":"martinetz","journal-title":"A” neural-gas” network learns topologies","key":"ref9"},{"key":"ref1","first-page":"281","article-title":"Some methods for classification and analysis of multivariate observations","volume":"1","author":"macqueen","year":"1967","journal-title":"Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability"},{"doi-asserted-by":"publisher","key":"ref20","DOI":"10.1038\/s41592-018-0019-x"},{"doi-asserted-by":"publisher","key":"ref22","DOI":"10.1162\/neco.1989.1.4.541"},{"doi-asserted-by":"publisher","key":"ref21","DOI":"10.1080\/14786440109462720"},{"key":"ref24","first-page":"3","article-title":"Autoencoders, minimum description length and helmholtz free energy","author":"hinton","year":"1994","journal-title":"Advances in neural information processing systems"},{"year":"1986","author":"smolensky","journal-title":"Information Processing in Dynamical Systems Foundations of Harmony Theory","key":"ref23"},{"key":"ref26","article-title":"Deep learning with nonparametric clustering","author":"chen","year":"2015","journal-title":"ArXiv Preprint"},{"key":"ref25","first-page":"478","article-title":"Unsupervised deep embedding for clustering analysis","author":"xie","year":"0","journal-title":"International Conference on Machine Learning"}],"event":{"name":"2021 International Joint Conference on Neural Networks (IJCNN)","start":{"date-parts":[[2021,7,18]]},"location":"Shenzhen, China","end":{"date-parts":[[2021,7,22]]}},"container-title":["2021 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9533266\/9533267\/09533411.pdf?arnumber=9533411","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T15:45:59Z","timestamp":1652197559000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9533411\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,18]]},"references-count":38,"URL":"https:\/\/doi.org\/10.1109\/ijcnn52387.2021.9533411","relation":{},"subject":[],"published":{"date-parts":[[2021,7,18]]}}}