We address the problem of learning a kernel for a given supervised learning task. Our approach consists in searching within the convex hull of a prescribed set of basic kernels fo...
Andreas Argyriou, Raphael Hauser, Charles A. Micch...
The concept of generalized cases has been proven useful when searching for configurable and flexible products, for instance, reusable components in the area of electronic design au...
Alexander Tartakovski, Martin Schaaf, Rainer Maxim...
We introduce Hegel and Fichte’s dialectic as a search meta-heuristic for constraint satisfaction and optimization. Dialectic is an appealing mental concept for local search as it...
The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) is a variable-metric algorithm for real-valued vector optimization. It maintains a parent population...
Geometric Particle Swarm Optimization (GPSO) is a recently introduced formal generalization of traditional Particle Swarm Optimization (PSO) that applies naturally to both continu...