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DTSTART:20240310T070000
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DTSTART;TZID=America/Toronto:20241115T153000
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URL:/combinatorics-and-optimization/events/tutte-colloq
 uium-guoyin-li
SUMMARY:Tutte colloquium-Guoyin Li
CLASS:PUBLIC
DESCRIPTION:Summary \n\nTITLE: Proximal methods for nonsmooth and nonconvex
  fractional\nprograms: when sparse optimization meets fractional programs\
 n\nSPEAKER:\n Guoyin Li\n\nAFFILIATION:\n University of New South Wales \n
 \nLOCATION:\n MC 5501\n\nABSTRACT:Nonsmooth and nonconvex fractional progr
 ams are ubiquitous\nand also highly challenging. It includes the composite
  optimization\nproblems studied extensively lately\, and encompasses many 
 important\nmodern optimization problems arising from diverse areas such as
  the\nrecent proposed scale invariant sparse signal reconstruction problem
 \nin signal processing\, the robust Sharpe ratio optimization problems in\
 nfinance and the sparse generalized eigenvalue problem in\ndiscrimination 
 analysis. \n\nIn this talk\, we will introduce extrapolated proximal metho
 ds for\nsolving nonsmooth and nonconvex fractional programs and analyse th
 eir\nconvergence behaviour. Interestingly\, we will show that the proposed
 \nalgorithm exhibits linear convergence for the scale invariant sparse\nsi
 gnal reconstruction model\,  and the sparse generalized eigenvalue\nprobl
 em with either cardinality regularization or sparsity\nconstraints. This i
 s achieved by identifying the explicit\ndesingularization function of the 
 Kurdyka-_Ł_ ojasiewicz inequality\nfor the merit function of the fraction
 al optimization models. Finally\,\nif time permits\, we will present some 
 preliminary encouraging\nnumerical results for the proposed methods for sp
 arse signal\nreconstruction and sparse Fisher discriminant analysis\n\nThe
  talk is based on joint work with R.I. Bo ̧t\, M. Dao\, T.K. Pong\nand P.
  Yu.\n\n \n\n \n 
DTSTAMP:20250704T124820Z
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