Mingbin Feng – Optimization Online

Uniform Convergence of Sample Average Approximation with Adaptive Importance Sampling

Published: 2015/07/23, Updated: 2017/04/10

Stochastic Programming adaptive importance sampling, adaptive multiple importance sampling, parametric integration, sample average approximation, uniform convergence

We study sample average approximations under adaptive importance sampling. Based on a Banach-space-valued martingale strong law of large numbers, we establish uniform convergence of the sample average approximation to the function being approximated. In the optimization context, we obtain convergence of the optimal value and optimal solutions of the sample average approximation. Citation Technical Report … Read more

Complementarity Formulations of l0-norm Optimization Problems

Published: 2013/09/24, Updated: 2018/03/06

Complementarity and Variational Inequalities, Constrained Nonlinear Optimization complementarity constraints, l0-norm minimization, nonlinear programming

In a number of application areas, it is desirable to obtain sparse solutions. Minimizing the number of nonzeroes of the solution (its l0-norm) is a difficult nonconvex optimization problem, and is often approximated by the convex problem of minimizing the l1-norm. In contrast, we consider exact formulations as mathematical programs with complementarity constraints and their … Read more