5 papers
Decision-dependent distributionally robust standard quadratic optimization with Wasserstein ambiguity
Immanuel M. Bomze, Daniel de Vicente, Abdel Lisser +1
The standard quadratic optimization problem (StQP) consists of minimizing a quadratic form over the standard simplex. Without assuming convexity or concavity of the quadratic form,…
The Maximum Clique Problem under Adversarial Uncertainty: a min-max approach
Immanuel Bomze, Chiara Faccio, Francesco Rinaldi +1
We analyze the problem of identifying large cliques in graphs that are affected by adversarial uncertainty. More specifically, we consider a new formulation, namely the adversarial…
Uncertain standard quadratic optimization under distributional assumptions: a chance-constrained epigraphic approach
Immanuel M. Bomze, Daniel de Vicente
The standard quadratic optimization problem (StQP) consists of minimizing a quadratic form over the standard simplex. Without convexity or concavity of the quadratic form, the StQP…
Feature selection in linear SVMs via a hard cardinality constraint: a scalable SDP decomposition approach
Immanuel Bomze, Federico D'Onofrio, Laura Palagi +1
In this paper, we study the embedded feature selection problem in linear Support Vector Machines (SVMs), in which a cardinality constraint is employed, leading to an interpretable…
Finding quadratic underestimators for optimal value functions of nonconvex all-quadratic problems via copositive optimization
Markus Gabl, Immanuel Bomze
Modeling parts of an optimization problem as an optimal value function that depends on a top-level decision variable is a regular occurrence in optimization and an essential ingred…