Embarrassingly Shallow Autoencoders for Sparse Data
Embarrassingly Shallow Autoencoders for Sparse Data
Combining simple elements from the literature, we define a linear model that is geared toward sparse data, in particular implicit feedback data for recommender systems. We show that its training objective has a closed-form solution, and discuss the resulting conceptual insights. Surprisingly, this simple model achieves better ranking accuracy than …