2.7k citations · 4.6k across the 53 of their papers we have counts for
5 papers · 1 filter
Sequential Recommender Systems: Challenges, Progress and Prospects
Shoujin Wang, Liang Hu, Yan Wang +3
The emerging topic of sequential recommender systems has attracted increasing attention in recent years.Different from the conventional recommender systems including collaborative…
FiDi-RL: Incorporating Deep Reinforcement Learning with Finite-Difference Policy Search for Efficient Learning of Continuous Control
Longxiang Shi, Shijian Li, Longbing Cao +3
In recent years significant progress has been made in dealing with challenging problems using reinforcement learning.Despite its great success, reinforcement learning still faces c…
Multi-view Information-theoretic Co-clustering for Co-occurrence Data
Peng Xu, Zhaohong Deng, Kup-Sze Choi +2
Multi-view clustering has received much attention recently. Most of the existing multi-view clustering methods only focus on one-sided clustering. As the co-occurring data elements…
TBQ(): Improving Efficiency of Trace Utilization for Off-Policy Reinforcement Learning
Longxiang Shi, Shijian Li, Longbing Cao +2
Off-policy reinforcement learning with eligibility traces is challenging because of the discrepancy between target policy and behavior policy. One common approach is to measure the…
A Survey on Session-based Recommender Systems
Shoujin Wang, Longbing Cao, Yan Wang +3
Recommender systems (RSs) have been playing an increasingly important role for informed consumption, services, and decision-making in the overloaded information era and digitized e…