Gradient of Robust SVDD

22 Views Asked by At

In the process of opimizing the obj function in Robust SVDD. How to obtain the gradient of the objective function using the chain rule? $$J(R, c) = R + C \sum_{i=1}^N max(0,||x_i - c||-R)$$

R is the radius of the boundary and c is the vector representing the center of the boundary. And x_i is the one of the data points.