CBMM Memo Series: Recent submissions

Now showing items 4-6 of 147

    • Formation of Representations in Neural Networks 

      Ziyin, Liu; Chuang, Isaac; Galanti, Tomer; Poggio, Tomaso (Center for Brains, Minds and Machines (CBMM), 2024-10-07)
      Understanding neural representations will help open the black box of neural networks and advance our scientific understanding of modern AI systems. However, how complex, structured, and transferable representations emerge ...

    • On the Power of Decision Trees in Auto-Regressive Language Modeling 

      Gan, Yulu; Galanti, Tomer; Poggio, Tomaso; Malach, Eran (Center for Brains, Minds and Machines (CBMM), 2024-09-27)
      Originally proposed for handling time series data, Auto-regressive Decision Trees (ARDTs) have not yet been explored for language modeling. This paper delves into both the theoretical and practical applications of ARDTs ...

    • For HyperBFs AGOP is a greedy approximation to gradient descent 

      Gan, Yulu; Poggio, Tomaso (Center for Brains, Minds and Machines (CBMM), 2024-07-13)
      The Average Gradient Outer Product (AGOP) provides a novel approach to feature learning in neural networks. We applied both AGOP and Gradient Descent to learn the matrix M in the Hyper Basis Function Network (HyperBF) and ...