> Home > News

Novel math could bring machine learning to the next level

  1. 4.9.2019

    For an artificial vision machine to recognize human faces, for instance, it is typically necessary to previously train it by showing it thousands of images of human faces. However, not only is this process very time-consuming; it is also like a shot in the dark, because there is no control over what the machine learns during its training. Which facial features has it picked up to be able to do its job? No one really knows. The process works, but the machine itself behaves like black box.

    Couldn’t training become much faster if it were possible, beforehand, to inject into the machine some knowledge about the relevant features to look for in faces – or, for that matter, any other objects of interest? That’s exactly what the authors of the study asked themselves, and they answered the question affirmatively by resorting to a recent mathematical approach.

    “Allowing humans to drive the learning process of learning machines is fundamental to move towards a more intelligible artificial intelligence and reduce the skyrocketing cost in time and resources that current [learning machines] require in order to be trained”. – Mattia Bergomi

    Read the full story here

Latest Publications

  • Pardo-Vazquez JL, Castiñeiras-de Saa JR, Valente M, Damião I, Costa T, Vicente MI, Mendonça AG, Mainen ZF, Renart A (2019) The mechanistic foundation of Weber's law Nat. Neurosci. 22 (9)
  • Maia, A.; Oliveira, J.; Lajnef, M.; Mallet, L.; Tamouza, R.; Leboye, M.; Oliveira-Maia, A. J. (2019) Oxidative and nitrosative stress markers in obsessive-compulsive disorder: a systematic review and meta-analysis Acta Psychiatr Scand
  • Brugada-Ramentol, Victoria; Clemens, Ivar; de Polavieja, Gonzalo G. (2019) Active control as evidence in favor of sense of ownership in the moving Virtual Hand Illusion
  • Rao-Ruiz, Priyanka; Couey, Jonathan J.; Marcelo, Ivo M.; Bouwkamp, Christian G.; Slump, Denise E.; Matos, Mariana R.; van der Loo, Rolinka J.; Martins, Gabriela J.; van den Hout, Mirjam; van IJcken, Wilfred F.; Costa, Rui M.; van den Oever, Michel C.; Kus (2019) Engram-specific transcriptome profiling of contextual memory consolidation Nat Commun
  • Huber, Elizabeth; Henriques, Rafael Neto; Owen, Julia P.; Rokem, Ariel; Yeatman, Jason D. (2019) Applying microstructural models to understand the role of white matter in cognitive development