Research Article
Ranking Support Vector Machine with Kernel Approximation
Algorithm 3
RankSVM with kernel approximation.
Require: , , , | Ensure: | (1) Calculate the approximation embedding using the Nyström method or random Fourier features; | (2) Apply to training samples, ; | (3) repeat | (4) ; | (5) ; | (6) // Solve by linear CG | (7) repeat | (8) Update based on the computation of Hessian-vector multiplication, , for some vector ; | (9) until Convergence | (10) ; | (11) until Convergence of the Newton step |
|