multiple kernel learning

Robust Out-of-Distribution Stochastic Optimization with Heterogeneous Inclusive and Exclusive Distribution Clusters

Categories Infinite Dimensional Optimization, Robust Optimization, Stochastic Programming Tags , , , , , , , ,

Decision scenarios far from rare in practice often place data-driven decision-making in an awkward position, where the decision maker may have access to neither the target distribution itself nor any empirical samples drawn from it, especially when decisions must be made in novel or highly uncertain environments. In response, robust out-of-distribution stochastic optimization (RooDSO) has … Read more

Multiple Kernel Learning-Aided Column-and-Constraint Generation Method

Categories Applications - OR and Management Sciences, Optimization in Data Science, Robust Optimization Tags , , , ,

Two-stage robust optimization (two-stage RO), due to its ability to balance robustness and flexibility, has been widely used in various fields for decision-making under uncertainty. This paper proposes a multiple kernel learning (MKL)-aided column-and-constraint generation (CCG) method to address this issue in the context of data-driven decision optimization, and releases a corresponding registered Julia package, … Read more

Variable Neighborhood Search for parameter tuning in Support Vector Machines

Categories Data-Mining, Nonsmooth Optimization, Unconstrained Optimization Tags , , , , ,

As in most Data Mining procedures, how to tune the parameters of a Support Vector Machine (SVM) is a critical, though not sufficiently explored, issue. The default approach is a grid search in the parameter space, which becomes prohibitively time-consuming even when just a few parameters are to be tuned. For this reason, for models … Read more