Center for Brains, Minds & Machines: Recent submissions

Now showing items 61-63 of 159

    • 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 ...

    • The Language of Fake News: Opening the Black-Box of Deep Learning Based Detectors 

      O'Brien, Nicole; Latessa, Sophia; Evangelopoulos, Georgios; Boix, Xavier (Center for Brains, Minds and Machines (CBMM), 2018-11-01)
      The digital information age has generated new outlets for content creators to publish so-called “fake news”, a new form of propaganda that is intentionally designed to mislead the reader. With the widespread effects of the ...

    • Representations That Learn vs. Learning Representations 

      Liao, Qianli; Poggio, Tomaso (2018-12-31)
      During the last decade, we have witnessed tremendous progress in Machine Learning and especially the area of Deep Learning, a.k.a. “Learning Representations” (LearnRep for short). There is even an International Conference ...