# Vectorizing equation in MATLAB

I am working on collaborative filtering using matrix factorization in MATLAB. I am using Gradient Descent for parameter learning. The cost function to optimize is :

$J = {\left\| I \odot (R - U V') \right\|}_{F}^{2} + \lambda_1 {\left\| U \right\|}_{F}^{2} + \lambda_2 {\left\| V \right\|}_{F}^{2}$

I have the following equations for updates :

$\nabla J_{u(i)} = -\sum_j I_{ij} (r_{ij} - u_i v_j') v_j$

$\nabla J_{v(i)} = -\sum_j I_{ij} (r_{ij} - u_i v_j') u_i$

The dimensions of the matrices are :

$I -> n * n$

$R -> n*n$

$U -> n*k$

$V -> n*k$

I am not able to come up with vectorized form of the gradient, so I have to loop over i's and j's explicitly, which is slowing down the code a lot.

• 1) This kind of looks like one of Andrew NG's homework questions... is it? 2) What is the F subscript? – AN6U5 Jul 24 '16 at 15:50
• Also, 3) Is the "out of the page arrow" meant to be a vector dot product? 4) Why are you taking the lengths of vectors before squaring them? Its the same thing as just squaring them and will slow your code down. – AN6U5 Jul 24 '16 at 15:57
• How did you derive the gradients in the first place? Derive them in matrix form and voila. – Jim Sep 22 '16 at 19:54