Center for Brains, Minds & Machines: Recent submissions

Now showing items 94-96 of 159

    • On the Robustness of Convolutional Neural Networks to Internal Architecture and Weight Perturbations 

      Cheney, Nicholas; Schrimpf, Martin; Kreiman, Gabriel (Center for Brains, Minds and Machines (CBMM), arXiv, 2017-04-03)
      Deep convolutional neural networks are generally regarded as robust function approximators. So far, this intuition is based on perturbations to external stimuli such as the images to be classified. Here we explore the ...

    • Musings on Deep Learning: Properties of SGD 

      Zhang, Chiyuan; Liao, Qianli; Rakhlin, Alexander; Sridharan, Karthik; Miranda, Brando; e.a. (Center for Brains, Minds and Machines (CBMM), 2017-04-04)
      [previously titled "Theory of Deep Learning III: Generalization Properties of SGD"] In Theory III we characterize with a mix of theory and experiments the generalization properties of Stochastic Gradient Descent in ...

    • Theory II: Landscape of the Empirical Risk in Deep Learning 

      Poggio, Tomaso; Liao, Qianli (Center for Brains, Minds and Machines (CBMM), arXiv, 2017-03-30)
      Previous theoretical work on deep learning and neural network optimization tend to focus on avoiding saddle points and local minima. However, the practical observation is that, at least for the most successful Deep ...