{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,27]],"date-time":"2025-12-27T03:46:54Z","timestamp":1766807214308,"version":"3.28.0"},"reference-count":30,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,9]]},"DOI":"10.1109\/mlsp.2018.8516963","type":"proceedings-article","created":{"date-parts":[[2018,11,16]],"date-time":"2018-11-16T05:32:18Z","timestamp":1542346338000},"page":"1-6","source":"Crossref","is-referenced-by-count":8,"title":["SPARSE BAYESIAN BINARY LOGISTIC REGRESSION USING THE SPLIT-AND-AUGMENTED GIBBS SAMPLER"],"prefix":"10.1109","author":[{"given":"Maxime","family":"Vono","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicolas","family":"Dobigeon","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pierre","family":"Chainais","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref30","article-title":"On Markov chain Monte Carlo methods for tall data","author":"bardenet","year":"2017","journal-title":"J Mach Learn Res"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1993.10476321"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1214\/06-BA105"},{"key":"ref12","first-page":"111","author":"fr\u00fchwirth-schnatter","year":"2010","journal-title":"Data Augmentation and MCMC for Binary and Multinomial Logit Models"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1214\/12-BA719"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2013.829001"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/s11222-015-9567-4"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1137\/16M1108340"},{"key":"ref17","article-title":"Split-and-augmented Gibbs sampler - Application to large-scale inference problems","author":"vono","year":"2018","journal-title":"submitted"},{"key":"ref18","first-page":"101","article-title":"In defense of one-vs-all classification","volume":"5","author":"rifkin","year":"2004","journal-title":"J Mach Learn Res"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1198\/016214508000000337"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1090\/tran\/6911"},{"key":"ref4","first-page":"165","author":"agresti","year":"2003","journal-title":"Logistic Regression"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/2992274.2992275"},{"key":"ref3","first-page":"841","article-title":"On discriminative vs. generative classifiers: A comparison of logistic regression and naive Bayes","author":"ng","year":"2002","journal-title":"Advances in Neural Information Systems"},{"key":"ref6","doi-asserted-by":"crossref","DOI":"10.1007\/978-0-387-21606-5","author":"hastie","year":"2001","journal-title":"The Elements of Statistical Learning"},{"key":"ref29","first-page":"1058","article-title":"Regularization of neural networks using DropConnect","volume":"28","author":"wan","year":"2013","journal-title":"Proc Int Conf Machine Learning (ICML)"},{"key":"ref5","doi-asserted-by":"crossref","DOI":"10.1002\/9781118548387","volume":"398","author":"hosmer jr","year":"2013","journal-title":"Applied Logistic Regression"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/S0272-7757(96)00058-1"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1097\/00003246-199510000-00007"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/54.1-2.167"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1561\/2200000015"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1958.tb00292.x"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2003.1227989"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015435"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0437847100"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1137\/S1064827596304010"},{"key":"ref23","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1038\/381607a0","article-title":"Emergence of simple-cell receptive field properties by learning a sparse code for natural images","volume":"381","author":"olshausen","year":"1996","journal-title":"Nature"},{"journal-title":"A random block-coordinate Douglas-Rachford splitting method with low computational complexity for binary logistic regression","year":"2017","author":"briceno-arias","key":"ref26"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1198\/10618600152418584"}],"event":{"name":"2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP)","start":{"date-parts":[[2018,9,17]]},"location":"Aalborg","end":{"date-parts":[[2018,9,20]]}},"container-title":["2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8482103\/8516704\/08516963.pdf?arnumber=8516963","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,8,23]],"date-time":"2020-08-23T22:42:46Z","timestamp":1598222566000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8516963\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,9]]},"references-count":30,"URL":"https:\/\/doi.org\/10.1109\/mlsp.2018.8516963","relation":{},"subject":[],"published":{"date-parts":[[2018,9]]}}}