A Riemannian rank-adaptive method for low-rank optimizationZhou, Guifang;Huang, Wen;Gallivan, Kyle A.;Van Dooren, Paul;Absil, Pierre-Antoine(2016) Neurocomputing — Vol. 192, p. 72-80 (2016)
Filesdocument.pdf Restricted Access Adobe PDF761.87 KBRequest a copyDetailsAuthorsZhou, GuifangFlorida State UniversityAuthorHuang, WenUCLouvainAuthorGallivan, Kyle A.Florida State UniversityAuthorVan Dooren, PaulFlorida State UniversityAuthorAbsil, Pierre-AntoineUCLouvainAuthorAffiliationsUCLouvainSST/ICTM/INMA - Pôle en ingénierie mathématiqueShow moreCitations APA Chicago FWB Zhou, G., Huang, W., Gallivan, K. A., Van Dooren, P., & Absil, P.-A. (2016). A Riemannian rank-adaptive method for low-rank optimization. Neurocomputing, 192, 72-80. https://doi.org/10.1016/j.neucom.2016.02.030 (Original work published 2016)