11 citations · 14 across the 5 of their papers we have counts for
4 papers · 1 filter
Attentive Autoencoders for Multifaceted Preference Learning in One-class Collaborative Filtering
Zheda Mai, Ga Wu, Kai Luo +1
Most existing One-Class Collaborative Filtering (OC-CF) algorithms estimate a user's preference as a latent vector by encoding their historical interactions. However, users often s…
Noise Contrastive Estimation for Autoencoding-based One-Class Collaborative Filtering
Jin Peng Zhou, Ga Wu, Zheda Mai +1
One-class collaborative filtering (OC-CF) is a common class of recommendation problem where only the positive class is explicitly observed (e.g., purchases, clicks). Autoencoder ba…
Noise Contrastive Estimation for Scalable Linear Models for One-Class Collaborative Filtering
Ga Wu, Maksims Volkovs, Chee Loong Soon +2
Previous highly scalable one-class collaborative filtering methods such as Projected Linear Recommendation (PLRec) have advocated using fast randomized SVD to embed items into a la…
Aesthetic Features for Personalized Photo Recommendation
Yu Qing Zhou, Ga Wu, Scott Sanner +1
Many photography websites such as Flickr, 500px, Unsplash, and Adobe Behance are used by amateur and professional photography enthusiasts. Unlike content-based image search, such u…