Track 11 Chair(s)

Andrea Acquaviva, Politecnico di Torino, Italy

 

 

Track 11 PC members

  • TBC

Topics of Interest

  • Conventional hardware (i.e. VLSI, FPGAs) and innovative hardware (i.e., memristor) implementation of Neuromorphic systems
  • Algorithm, and architecture co-optimization for efficient machine-learning hardware design
  • Models for neurons and synapses;
  • Spiking neuro-inspired architectures building blocks;
  • Reliable communication networks for neuro-inspired chips/systems;
  • Reconfigurability and adaptability methods;
  • Deep learning models;
  • New applications of on-chip learning (i.e., mobile devices, IoT).