https://www.nber.org/papers/w31868
Identification using Revealed Preferences in Linearly Separable Models | NBER
Founded in 1920, the NBER is a private, non-profit, non-partisan organization dedicated to conducting economic research and to disseminating research findings...
revealed preferenceslinearly separableidentificationusingmodels
https://openreview.net/forum?id=sACJw28GV4
Understanding How Nonlinear Networks Create Linearly Separable Features for Low-Dimensional Data |...
Deep neural networks have attained remarkable success across diverse classification tasks. Recent empirical studies have shown that deep networks learn...
linearly separable