Accelerating DNN Training Through Selective Localized Learning - Krithivasan, Sarada; Sen, Sanchari; Venkataramani, Swagath; Raghunathan, Anand (Frontiers in Neuroscience, 2022)
Training Deep Neural Networks (DNNs) places immense compute requirements on the underlying hardware platforms, expending large amounts of time and energy. We propose Local+SGD, a new algorithmic approach to accelerate DNN training by selectively combining localized or Hebbian learning within a Stochastic Gradient Descent (SGD) based training framework