54 citations · 100 across the 12 of their papers we have counts for
6 papers · 1 filter
ProFairRec: Provider Fairness-aware News Recommendation
Tao Qi, Fangzhao Wu, Chuhan Wu +5
News recommendation aims to help online news platform users find their preferred news articles. Existing news recommendation methods usually learn models from historical user behav…
Reinforcement Routing on Proximity Graph for Efficient Recommendation
Chao Feng, Defu Lian, Xiting Wang +3
We focus on Maximum Inner Product Search (MIPS), which is an essential problem in many machine learning communities. Given a query, MIPS finds the most similar items with the maxim…
Learning Fair Representations for Recommendation: A Graph-based Perspective
Le Wu, Lei Chen, Pengyang Shao +3
As a key application of artificial intelligence, recommender systems are among the most pervasive computer aided systems to help users find potential items of interests. Recently,…
FairRec: Fairness-aware News Recommendation with Decomposed Adversarial Learning
Chuhan Wu, Fangzhao Wu, Xiting Wang +2
News recommendation is important for online news services. Existing news recommendation models are usually learned from users' news click behaviors. Usually the behaviors of users…
A Neural Influence Diffusion Model for Social Recommendation
Le Wu, Peijie Sun, Yanjie Fu +3
Precise user and item embedding learning is the key to building a successful recommender system. Traditionally, Collaborative Filtering(CF) provides a way to learn user and item em…
SocialGCN: An Efficient Graph Convolutional Network based Model for Social Recommendation
Le Wu, Peijie Sun, Richang Hong +3
Collaborative Filtering (CF) is one of the most successful approaches for recommender systems. With the emergence of online social networks, social recommendation has become a popu…