Machine Learning, Optimization, Gradient Descent, Reinforcement Learning.
relevant variables, this will be useful to refer back to during the discussion. b: a Bernoulli r.v. This is our discrete choice. b takes on the values {0, 1}. b is analogous to z in Gumbel softmax. z: the “logit” of the softmax, it is analogous to log(π+g) for our Gumbel softmax formulation. We’re