Recent Advances in Recommender Systems: Matrices, Bandits, and Blenders
On the challenges of learning with inference networks on sparse, high-dimensional data
Using Image Fairness Representations in Diversity-Based Re-ranking for Recommendations
NeuRec: On Nonlinear Transformation for Personalized Ranking
Local Latent Space Models for Top-N Recommendation
Personalized recommendation with implicit feedback via learning pairwise preferences over item-sets