40 citations · 72 across the 4 of their papers we have counts for
3 papers · 1 filter
Semi-supervised Adversarial Learning for Complementary Item Recommendation
Koby Bibas, Oren Sar Shalom, Dietmar Jannach
Complementary item recommendations are a ubiquitous feature of modern e-commerce sites. Such recommendations are highly effective when they are based on collaborative signals like…
Rank and Rate: Multi-task Learning for Recommender Systems
Guy Hadash, Oren Sar Shalom, Rita Osadchy
The two main tasks in the Recommender Systems domain are the ranking and rating prediction tasks. The rating prediction task aims at predicting to what extent a user would like any…
Privacy and Fairness in Recommender Systems via Adversarial Training of User Representations
Yehezkel S. Resheff, Yanai Elazar, Moni Shahar +1
Latent factor models for recommender systems represent users and items as low dimensional vectors. Privacy risks of such systems have previously been studied mostly in the context…