{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T21:40:08Z","timestamp":1750369208038,"version":"3.41.0"},"reference-count":37,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,3]]},"DOI":"10.1109\/icassp.2017.7952555","type":"proceedings-article","created":{"date-parts":[[2017,6,20]],"date-time":"2017-06-20T21:35:36Z","timestamp":1497994536000},"page":"2242-2246","source":"Crossref","is-referenced-by-count":1,"title":["Parallelized Stochastic Gradient Markov Chain Monte Carlo algorithms for non-negative matrix factorization"],"prefix":"10.1109","author":[{"given":"Umut","family":"Simsekli","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alain","family":"Durmus","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Roland","family":"Badeau","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gael","family":"Richard","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eric","family":"Moulines","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"A. Taylan","family":"Cemgil","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref33","article-title":"MCMC using Hamiltonian dynamics","volume":"54","author":"neal","year":"2010","journal-title":"Handbook of Markov Chain Monte Carlo"},{"journal-title":"Parallel stochastic gradient Markov chain Monte Carlo for matrix factorisation models","year":"2015","author":"?im?ekli","key":"ref32"},{"key":"ref31","article-title":"Stochastic quasi-Newton Langevin Monte Carlo","author":"?im?ekli","year":"2016","journal-title":"ICML"},{"key":"ref30","doi-asserted-by":"crossref","DOI":"10.1609\/aaai.v30i1.10200","article-title":"Preconditioned stochastic gradient Langevin dynamics for deep neural networks","author":"li","year":"2016","journal-title":"AAAI Conference on Artificial Intelligence"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/SSP.2011.5967665"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1155\/2009\/785152"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1364\/AO.36.008352"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ACV.1994.341300"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783373"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390267"},{"key":"ref12","article-title":"Stochastic gradient Richardson-Romberg Markov chain Monte Carlo","author":"durmus","year":"2016","journal-title":"NIPS"},{"journal-title":"The theory of dispersion models","year":"1997","author":"j\u00f8rgensen","key":"ref13"},{"key":"ref14","first-page":"1409","article-title":"Learning the beta-divergence in Tweedie compound Poisson matrix factorization models","author":"?im?ekli","year":"2013","journal-title":"ICML"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2366144"},{"key":"ref16","first-page":"2120","article-title":"Learning mixed divergences in coupled matrix and tensor factorization models","author":"?im?ekli","year":"2015","journal-title":"ICASSP"},{"key":"ref17","first-page":"1","article-title":"Optimal weight learning for coupled tensor factorization with mixed divergences","author":"?im?ekli","year":"2013","journal-title":"EUSIPCO"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177729586"},{"key":"ref19","first-page":"681","article-title":"Bayesian learning via Stochastic Gradient Langevin Dynamics","author":"welling","year":"2011","journal-title":"ICML"},{"key":"ref28","first-page":"37","article-title":"Covariance-controlled adaptive Langevin thermostat for large-scale Bayesian sampling","author":"shang","year":"2015","journal-title":"NIPS"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1002\/9780470747278"},{"key":"ref27","first-page":"3203","article-title":"Bayesian sampling using stochastic gradient thermostats","author":"ding","year":"2014","journal-title":"NIPS"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1000029"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/1772690.1772760"},{"key":"ref29","first-page":"2899","article-title":"A complete recipe for stochastic gradient MCMC","author":"ma","year":"2015","journal-title":"NIPS"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1162\/neco.2008.04-08-771"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/s12532-013-0053-8"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/2020408.2020426"},{"key":"ref2","first-page":"177","author":"smaragdis","year":"2003","journal-title":"Non-negative Matrix Factorization for Polyphonic Music Transcription"},{"key":"ref9","article-title":"Stochastic thermodynamic integration: efficient Bayesian model selection via stochastic gradient MCMC","author":"?im?ekli","year":"2016","journal-title":"ICASSP"},{"key":"ref1","doi-asserted-by":"crossref","DOI":"10.1038\/44565","article-title":"Learning the parts of objects by non-negative matrix factorization","volume":"401","author":"lee","year":"1999","journal-title":"Nature"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.2307\/3318418"},{"key":"ref22","first-page":"1","article-title":"Consistency and fluctuations for stochastic gradient Langevin dynamics","volume":"17","author":"teh","year":"2016","journal-title":"Journal of Machine Learning Research"},{"key":"ref21","first-page":"982","article-title":"Approximation analysis of stochastic gradient Langevin dynamics by using Fokker-Planck equation and Ito process","author":"sato","year":"2014","journal-title":"ICML"},{"key":"ref24","article-title":"Bayesian posterior sampling via stochastic gradient Fisher scoring","author":"ahn","year":"2012","journal-title":"ICML"},{"key":"ref23","first-page":"2269","article-title":"On the convergence of stochastic gradient MCMC algorithms with high-order integrators","author":"chen","year":"2015","journal-title":"NIPS"},{"key":"ref26","article-title":"Stochastic gradient Hamiltonian Monte Carlo","author":"chen","year":"2014","journal-title":"ICML"},{"key":"ref25","article-title":"Stochastic gradient Riemannian Langevin dynamics on the probability simplex","author":"patterson","year":"2013","journal-title":"NIPS"}],"event":{"name":"2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","start":{"date-parts":[[2017,3,5]]},"location":"New Orleans, LA","end":{"date-parts":[[2017,3,9]]}},"container-title":["2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7943262\/7951776\/07952555.pdf?arnumber=7952555","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T21:00:02Z","timestamp":1750366802000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7952555\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,3]]},"references-count":37,"URL":"https:\/\/doi.org\/10.1109\/icassp.2017.7952555","relation":{},"subject":[],"published":{"date-parts":[[2017,3]]}}}