This work presents a discriminative training method for
particle filters in the context of multi-object tracking. We
are motivated by the difficulty of hand-tuning the many
mode...
Abstract. In this paper, we elaborate how decision space diversity can be integrated into indicator-based multiobjective search. We introduce DIOP, the diversity integrating multio...
In Multi-Objective Problems (MOPs) involving uncertainty, each solution might be associated with a cluster of performances in the objective space depending on the possible scenari...
Abstract. Real-world optimization problems are often subject to uncertainties, which can arise regarding stochastic model parameters, objective functions and decision variables. Th...
—Multi-objective optimization is an essential and challenging topic in the domains of engineering and computation because real-world problems usually include several conflicting...