BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Michael Ng (University of Hong Kong) DTSTART:20200722T140000Z DTEND:20200722T150000Z DTSTAMP:20260423T022915Z UID:E-NLA/14 DESCRIPTION:Title: N onnegative low rank matrix approximation and its applications\nby Mich ael Ng (University of Hong Kong) as part of E-NLA - Online seminar series on numerical linear algebra\n\n\nAbstract\nIn this talk\, we study low ran k matrix approximation (NLRM) for nonnegative matrices arising from many d ata mining and pattern recognition applications. Our approach is different from classical nonnegative matrix factorization (NMF) which has been stud ied for some time. For a given nonnegative matrix\, the usual NMF approach is to determine two nonnegative low rank matrices such that the distance between their product and the given nonnegative matrix is as small as poss ible. However\, the proposed NLRM approach is to determine a nonnegative l ow rank matrix such that the distance between such matrix and the given no nnegative matrix is as small as possible. There are two advantages. (i) Th e minimized distance can be smaller. (ii) The proposed method can identify important singular basis vectors\, while this information may not be obta ined in the classical NMF. Numerical results are reported to demonstrate t he performance of the proposed method. Several extensions and research wor ks are also presented.\n\nThis talk describes joint work with Tai-Xiang Ji ang (Southwestern University of Finance and Economics)\, JunJun Pan (Unive rsite de Mons)\, Guang-Jing Song (Weifang University) and Hong Zhu (Jiangs u University).\n LOCATION:https://researchseminars.org/talk/E-NLA/14/ END:VEVENT END:VCALENDAR