28 citations · 60 across the 7 of their papers we have counts for
3 papers · 1 filter
One-class Recommendation Systems with the Hinge Pairwise Distance Loss and Orthogonal Representations
Ramin Raziperchikolaei, Young-joo Chung
In one-class recommendation systems, the goal is to learn a model from a small set of interacted users and items and then identify the positively-related user-item pairs among a la…
Simultaneous Learning of the Inputs and Parameters in Neural Collaborative Filtering
Ramin Raziperchikolaei, Young-joo Chung
Neural network-based collaborative filtering systems focus on designing network architectures to learn better representations while fixing the input to the user/item interaction ve…
Neural Representations in Hybrid Recommender Systems: Prediction versus Regularization
Ramin Raziperchikolaei, Tianyu Li, Young-joo Chung
Autoencoder-based hybrid recommender systems have become popular recently because of their ability to learn user and item representations by reconstructing various information sour…