Machine Learning, Optimization, Gradient Descent, Reinforcement Learning.
form that expects over b instead of z. ** ẑ =g(v, b, θ) is a differentiable and deterministic function that maps b back to logit space. It can be shown that g exists for our current setup. The second term takes the exact form we want for our baseline with c=E_p(v)[f(σ_λ(ẑ))]. If we were to subtract