4 papers · 1 filter
0/1 Constrained Optimization Solving Sample Average Approximation for Chance Constrained Programming
Shenglong Zhou, Lili Pan, Naihua Xiu +1
Sample average approximation (SAA) is a tractable approach for dealing with chance constrained programming, a challenging stochastic optimization problem. The constraint of SAA is…
An Oracle Gradient Regularized Newton Method for Quadratic Measurements Regression
Jun Fan, Jie Sun, Ailing Yan +1
Recovering an unknown signal from quadratic measurements has gained popularity due to its wide range of applications, including phase retrieval, fusion frame phase retrieval, and p…
Nonconvex quasi-variational inequalities: stability analysis and application to numerical optimization
Joydeep Dutta, Lahoussine Lafhim, Alain Zemkoho +1
We consider a parametric quasi-variational inequality (QVI) without any convexity assumption. Using the concept of \emph{optimal value function}, we transform the problem into that…
Revisiting Norm Regularized Optimization
Shenglong Zhou, Xianchao Xiu, Yingnan Wang +1
Sparse optimization has seen its advances in recent decades. For scenarios where the true sparsity is unknown, regularization turns out to be a promising solution. Two popular non-…