Collaborative Filtering, Matrix Factorization, Recommender Systems, Gradient Descent, Neural Networks.
every iteration: Update equation for U, where alpha is the learning rate (image by author) Update equation for V, where alpha is the learning rate (image by author) Training Regime with the Linear Model Here is some simple code that iteratively optimizes U and V to reconstruct R more accurately