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Mainstream surrogate approaches for multi-objective problems build one approximation for each objective. Mono-surrogate approaches instead aim at characterizing the Pareto front with a single model. Such an approach has been recently introduced using a mix ...
Recommender systems have become important, as users are faced with an ever-increasing amount of information available on internet. Much of the research work on the topic has been focused on recommendation techniques, aiming at improving the accuracy of rec ...
This paper deals with the influence of age progression on the performance of face verification systems. This is a challenging and largely open research problem that deserves more and more attention. Aging affects both the shape of the face and its texture, ...
We investigate the effect of Dzyaloshinskii-Moriya (DM) interactions on torque measurements of quantum magnets with magnetization plateaux in the context of a frustrated spin-1/2 ladder. Using extensive DMRG simulations, we show that the DM contribution to ...
A semi-distributed hydrological model was developed for the upper Rhone River basin in Switzerland to provide 72 h lead time discharge forecasts for the optimization of a multireservoir system during floods The performance of the model is presented and cor ...
Over the last years, international sea freight container transportation has grown dramatically and container terminals play nowadays a key role within the global shipping network. Terminals operations have received increasing interest in the scientific lit ...
Over the last years, international sea freight container transportation has grown dramatically and container terminals play nowadays a key role within the global shipping network. Terminal's operations have received increasing interest in the scientific li ...
We present an effective method to optimize over the parameters of an image patch descriptor to obtain one that is computationally more efficient while maintaining a high recognition rate. We formulate the optimization problem in a multi-objective manner, w ...
Dynamic stochastic optimization problems with a large (possibly infinite) number of decision stages and high-dimensional state vectors are inherently difficult to solve. In fact, scenario tree-based algorithms are unsuitable for problems with many stages, ...
This article describes a bounding approximation scheme for convex multistage stochastic programs (MSP) that constrain the conditional expectation of some decision-dependent random variables. Expected value constraints of this type are useful for modelling ...