Artificial Intelligence, Machine Learning, Deep Learning, Neural Networks.
past squared gradients. m=β*m — (1-β)∇J(θ​) s = ρ*s + (1-ρ)∇J(θ​) ⦻ ∇J(θ​) m*=m/(1-β) s*=s/(1-ρ) θ​=θ​+α*m divided by √(s+ε) division here is element-wise Adam has become the choice of optimizer since it outperforms all momentum and adaptive optimizers Adam has another variant which is quite