• DocumentCode
    184949
  • Title

    The pseudomonotone stochastic variational inequality problem: Analytical statements and stochastic extragradient schemes

  • Author

    Kannan, Ajaykumar ; Shanbhag, Uday V.

  • Author_Institution
    Dept. of Ind. & Manuf. Eng., Pennsylvania State Univ., University Park, PA, USA
  • fYear
    2014
  • fDate
    4-6 June 2014
  • Firstpage
    2930
  • Lastpage
    2935
  • Abstract
    Variational inequality problems find wide applicability in modeling a range of optimization and equilibrium problems. We consider the stochastic generalization of such a problem wherein the mapping is pseudomonotone and make two sets of contributions in this paper. First, we provide sufficiency conditions for the solvability of such problems that do not require evaluating the expectation. Second, we consider an extragradient variant of stochastic approximation for the solution of such problems and under suitable conditions, show that this scheme produces iterates that converge in an almost-sure sense.
  • Keywords
    approximation theory; computability; gradient methods; optimisation; stochastic processes; variational techniques; extragradient variant; optimization; pseudomonotone stochastic variational inequality problem; solvability; stochastic approximation; stochastic extragradient schemes; stochastic generalization; sufficiency condition; Approximation methods; Convergence; Educational institutions; Optimization; Standards; Stochastic processes; Vectors; Optimization; Optimization algorithms; Randomized algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2014
  • Conference_Location
    Portland, OR
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4799-3272-6
  • Type

    conf

  • DOI
    10.1109/ACC.2014.6859377
  • Filename
    6859377