CBMM Memo Series: Recent submissions

Now showing items 55-57 of 149

    • An analysis of training and generalization errors in shallow and deep networks 

      Mhaskar, H.N.; Poggio, Tomaso (Center for Brains, Minds and Machines (CBMM), arXiv.org, 2019-05-30)
      This paper is motivated by an open problem around deep networks, namely, the apparent absence of overfitting despite large over-parametrization which allows perfect fitting of the training data. In this paper, we analyze ...

    • Biologically-plausible learning algorithms can scale to large datasets 

      Xiao, Will; Chen, Honglin; Liao, Qianli; Poggio, Tomaso (Center for Brains, Minds and Machines (CBMM), arXiv.org, 2018-11-08)
      The backpropagation (BP) algorithm is often thought to be biologically implausible in the brain. One of the main reasons is that BP requires symmetric weight matrices in the feedforward and feedback pathways. To address ...

    • What am I searching for? 

      Zhang, Mengmi; Feng, Jiashi; Lim, Joo Hwee; Zhao, Qi; Kreiman, Gabriel (Center for Brains, Minds and Machines (CBMM), arXiv.org, 2018-07-31)
      Can we infer intentions and goals from a person's actions? As an example of this family of problems, we consider here whether it is possible to decipher what a person is searching for by decoding their eye movement behavior. ...