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Article
Open AccessPure and mixed lexicographic-paretian many-objective optimization: state of the art
This work aims at reviewing the state of the art of the field of lexicographic multi/many-objective optimization. The discussion starts with a review of the literature, emphasizing the numerous application in ...
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Article
Open AccessPhotonic-aware neural networks
Photonics-based neural networks promise to outperform electronic counterparts, accelerating neural network computations while reducing power consumption and footprint. However, these solutions suffer from phys...
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Article
Open AccessThe Big-M method with the numerical infinite M
Linear programming is a very well known and deeply applied field of optimization theory. One of its most famous and used algorithms is the so called Simplex algorithm, independently proposed by Kantorovič and ...
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Article
Open AccessVectorizing posit operations on RISC-V for faster deep neural networks: experiments and comparison with ARM SVE
With the arrival of the open-source RISC-V processor architecture, there is the chance to rethink Deep Neural Networks (DNNs) and information representation and processing. In this work, we will exploit the fo...
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Article
Open AccessA maritime decision support system to assess risk in the presence of environmental uncertainties: the REP10 experiment
The aim of this work is to report on an activity carried out during the 2010 Recognized Environmental Picture experiment, held in the Ligurian Sea during summer 2010. The activity was the first at-sea test of ...
