Publications: Recent submissions

Now showing items 52-54 of 160

    • Do Neural Networks for Segmentation Understand Insideness? 

      Villalobos, Kimberly; Štih, Vilim; Ahmadinejad, Amineh; Sundaram, Shobhita; Dozier, Jamell; e.a. (Center for Brains, Minds and Machines (CBMM), 2020-04-04)
      The insideness problem is an image segmentation modality that consists of determining which pixels are inside and outside a region. Deep Neural Networks (DNNs) excel in segmentation benchmarks, but it is unclear that they ...

    • Can we Contain Covid-19 without Locking-down the Economy? 

      Shalev-Shwartz, Shai; Shashua, Amnon (Center for Brains, Minds and Machines (CBMM), 2020-03-26)
      We present an analysis of a risk-based selective quarantine model where the population is divided into low and high-risk groups. The high-risk group is quarantined until the low-risk group achieves herd-immunity. We tackle ...

    • Stable Foundations for Learning: a foundational framework for learning theory in both the classical and modern regime. 

      Poggio, Tomaso (Center for Brains, Minds and Machines (CBMM), 2020-03-25)
      We consider here the class of supervised learning algorithms known as Empirical Risk Minimization (ERM). The classical theory by Vapnik and others characterize universal consistency of ERM in the classical regime in which ...