{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,29]],"date-time":"2025-09-29T08:05:22Z","timestamp":1759133122087,"version":"3.37.3"},"reference-count":37,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"8","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Comput."],"published-print":{"date-parts":[[2021,8,1]]},"DOI":"10.1109\/tc.2021.3064301","type":"journal-article","created":{"date-parts":[[2021,3,8]],"date-time":"2021-03-08T21:41:05Z","timestamp":1615239665000},"page":"1189-1198","source":"Crossref","is-referenced-by-count":3,"title":["Minimal Complexity Machines Under Weight Quantization"],"prefix":"10.1109","volume":"70","author":[{"given":"Mayank","family":"Sharma","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1926-3065","authenticated-orcid":false,"given":"Sumit","family":"Soman","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0604-8756","authenticated-orcid":false,"family":"Jayadeva","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.23919\/ECC.2013.6669541"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2015.2504382"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2004.1334035"},{"key":"ref30","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2015","journal-title":"Proc 3rd Int Conf Learn Representations"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/2641190.2641198"},{"journal-title":"Foundations of Machine Learning","year":"2012","author":"mohri","key":"ref36"},{"key":"ref35","first-page":"682","article-title":"Using the nystr&#x00F6;m method to speed up kernel machines","author":"williams","year":"2000","journal-title":"Proc 13th Int Conf Neural Inf Process Syst"},{"key":"ref34","first-page":"83:1","article-title":"CVXPY: A Python-embedded modeling language for convex optimization","volume":"17","author":"diamond","year":"2016","journal-title":"J Mach Learn Res"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/FCCM.2009.34"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2012.2196446"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/tc.2011.113"},{"journal-title":"Statistical Learning Theory","year":"1998","author":"vapnik","key":"ref13"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1023\/A:1009715923555"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/1961189.1961199"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/BF00994018"},{"key":"ref17","first-page":"10","article-title":"LS-SVMlab toolbox user's guide","author":"de brabanter","year":"0"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1023\/A:1018628609742"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.1999.831072"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2010.01.024"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/811"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2014.2333879"},{"key":"ref3","first-page":"4107","article-title":"Binarized neural networks","author":"hubara","year":"2016","journal-title":"Proc 30th Int Conf Neural Inf Process Syst"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2005.1555933"},{"key":"ref29","first-page":"265","article-title":"On the algorithmic implementation of multiclass kernel-based vector machines","volume":"2","author":"crammer","year":"2001","journal-title":"J Mach Learn Res"},{"key":"ref5","first-page":"168","article-title":"Embedded binarized neural networks","author":"mcdanel","year":"2017","journal-title":"Proc Int Conf Embedded Wireless Syst Netw"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1142\/S0218001403002472"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2003.816345"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1117\/1.JEI.27.1.013020"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/DSD.2004.1333285"},{"key":"ref1","first-page":"187:1","article-title":"Quantized neural networks: Training neural networks with low precision weights and activations","volume":"18","author":"hubara","year":"2017","journal-title":"J Mach Learn Res"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2018.8489089"},{"key":"ref22","doi-asserted-by":"crossref","first-page":"1610","DOI":"10.1016\/j.neucom.2015.06.065","article-title":"Learning a hyperplane regressor through a tight bound on the VC dimension","volume":"171","author":"chandra","year":"2016","journal-title":"Neurocomputing"},{"key":"ref21","doi-asserted-by":"crossref","first-page":"881","DOI":"10.1007\/s11063-018-9793-9","article-title":"Ultra-sparse classifiers through minimizing the VC dimension in the empirical feature space - Submitted to the special issue on &#x201D;off the mainstream: Advances in neural networks and machine learning for pattern recognition","volume":"48","author":"sharma","year":"2018","journal-title":"Neural Process Lett"},{"key":"ref24","first-page":"1","article-title":"The MC-ELM: Learning an ELM-like network with minimum VC dimension","author":"soman","year":"2015","journal-title":"Proc Int Joint Conf Neural Netw"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2014.07.062"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/76359.76371"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2017.2694321"}],"container-title":["IEEE Transactions on Computers"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/12\/9478065\/09372849.pdf?arnumber=9372849","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,27]],"date-time":"2022-01-27T21:23:17Z","timestamp":1643318597000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9372849\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,1]]},"references-count":37,"journal-issue":{"issue":"8"},"URL":"https:\/\/doi.org\/10.1109\/tc.2021.3064301","relation":{},"ISSN":["0018-9340","1557-9956","2326-3814"],"issn-type":[{"type":"print","value":"0018-9340"},{"type":"electronic","value":"1557-9956"},{"type":"electronic","value":"2326-3814"}],"subject":[],"published":{"date-parts":[[2021,8,1]]}}}