Balancing Between Accuracy and Fairness for Interactive Recommendation with Reinforcement Learning.
Weiwen LiuFeng LiuRuiming TangBen LiaoGuangyong ChenPheng-Ann HengPublished in: PAKDD (1) (2020)
Keyphrases
- reinforcement learning
- high accuracy
- computational cost
- collaborative filtering
- function approximation
- highly accurate
- prediction accuracy
- error rate
- recommendation algorithms
- data sets
- state space
- learning process
- recommender systems
- virtual reality
- high precision
- computational efficiency
- learning problems
- multi agent
- recommendation systems
- e learning