Maurici Yagües

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Deep neural networks have gained popularity inrecent years, obtaining outstanding results in a wide range ofapplications such as computer vision in both academia andmultiple industry areas. The progress made in recent years cannotbe understood without taking into account the technologicaladvancements seen in key domains such as High PerformanceComputing,(More)
Deep learning algorithms base their success on building high learning capacity models with millions of parameters that are tuned in a data-driven fashion. These models are trained by processing millions of examples, so that the development of more accurate algorithms is usually limited by the throughput of the computing devices on which they are trained. In(More)
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