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Infeasible interior-point algorithms based on sampling average approximations for a class of stochastic complementarity problems and their applications.

Zhen-Ping YangJin ZhangXide ZhuGui-Hua Lin
Published in: J. Comput. Appl. Math. (2019)
Keyphrases
  • complementarity problems
  • computational complexity
  • interior point
  • learning algorithm
  • lower bound
  • optimization problems
  • linear programming
  • multistage
  • linear complementarity problem