We present a novel solution to the MediaEval 2014 Event Synchronization Task: Synchronization of Multi-User Event Media (SEM). The framework is based on a probabilistic graphical model. Thanks to the simple topology of the graph, the estimation of the true temporal displacement among multiple photo collections can be performed efficiently through exact inference. The underlying fitness function...

Abstract In the present paper, fundamental frequency optimization of symmetrically laminated composite plates is studied using the combination of Elitist-Genetic algorithm (E-GA) and finite strip method (FSM). The design variables are the number of layers, the fiber orientation angles, edge conditions and plate length/width ratios. The classical laminated plate theory is used to calculate the n...

Multi-objective formulations are realistic models for many complex engineering optimization problems. In many real-life problems, objectives under consideration conflict with each other, and optimizing a particular solution with respect to a single objective can result in unacceptable results with respect to the other objectives. A reasonable solution to a multi-objective problem is to investig...

The performance of an information retrieval system is usually measured in terms of two different criteria, precision and recall. This way, the optimization of any of its components is a clear example of a multiobjective problem. However, although evolutionary programming have been widely applied in the information retrieval area, in all of these applications both criteria have been combined in ...

This paper introduces a new iterative evolutionary algorithm, which is able to provide an evenly distributed set of solutions in multiobjective context. The method is different from the other evolutionary algorithms in two perspectives. First, instead of density information incorporated to find a diverse set of solutions, a hypercylinder is introduced as a new constraint to the problem. Searchi...

The aim of this paper is to clearly demonstrate the potential ability of a similarity-based mating scheme to dynamically control the balance between the diversity of solutions and the convergence to the Pareto front in evolutionary multiobjective optimization. The similarity-based mating scheme chooses two parents in the following manner. For choosing one parent (say Parent A), first a pre-spec...

Recently it has been demonstrated that collaboration between automated algorithms and human users can be especially effective in robot behavior optimization tasks. In particular, we recently introduced a Fitness-based Search with Preferencebased Policy Learning (FS-PPL) approach, in which the algorithm models the user based on her preferences and then uses the model, along with the fitness func...

When developping multi-agent systems (MAS) or models in the context of agent-based simulation (ABS), the tuning of the model constitutes a crucial step of the design process. Indeed, agent-based models are generally characterized by lots of parameters, which together determine the global dynamics of the system. Moreover, small changes made to a single parameter sometimes lead to a radical modif...

Evolutionary algorithms have shown some success in solving multiobjective optimization problems. The methods of fitness assignment are mainly based on the information about the dominance relation between individuals. We propose a Pareto fitness genetic algorithm (PFGA) in which we introduce a modified ranking procedure and a promising way of sharing; a new fitness function based on the rank of ...

The goal of multi-objective clustering (MOC) is to decompose a dataset into similar groups maximizing multiple objectives in parallel. In this paper, we provide a methodology, architecture and algorithms that, based on a large set of objectives, derive interesting clusters regarding two or more of those objectives. The proposed architecture relies on clustering algorithms that support plug-in f...