Improved Estimation of Ranks for Learning Item Recommenders with Negative Sampling
Abstract
Growing number of recommendable items (# of movies, music, products).
Sample negative items to overcome computational cost of training on full set of negative items.
Rank is computed based on sample.
Sample negative items to overcome computational cost of training on full set of negative items.
Rank is computed based on sample.
