CBMM Memo Series: Recent submissions

Now showing items 13-15 of 146

    • Compositional Sparsity: a framework for ML 

      Poggio, Tomaso (Center for Brains, Minds and Machines (CBMM), 2022-10-10)
      The main claim of this perspective is that compositional sparsity of the target function, which corre- sponds to the task to be learned, is the key principle underlying machine learning. I prove that under restrictions of ...

    • Understanding the Role of Recurrent Connections in Assembly Calculus 

      Rangamani, Akshay; Xie, Yi (Center for Brains, Minds and Machines (CBMM), 2022-07-06)
      In this note, we explore the role of recurrent connections in Assembly Calculus through a number of experiments conducted on models with and without recurrent connections. We observe that as- semblies can be formed even ...

    • System identification of neural systems: If we got it right, would we know? 

      Han, Yena; Poggio, Tomaso; Cheung, Brian (Center for Brains, Minds and Machines (CBMM), 2022-07-02)
      Various artificial neural networks developed by engineers have been evaluated as models of the brain, such as the ventral stream in the primate visual cortex. After being trained on large datasets, the network outputs are ...