Mathematics, Machine Learning, Reinforcement Learning, Optimization.
only been able to remove the constraints but also reduced the number of parameters for optimization from an arbitrary neural network to just m+1 where m being the number of linear constraints and 1 for the quadratic constraint. Eqn (13) from Achiam Et al. 17 The above equation shows the final