Reinforcement learning serves as a potent tool for modeling dynamic user...
Recommendation models are typically trained on observational user intera...
Reinforcement learning-based recommender systems have recently gained
po...
Deep reinforcement learning (DRL) has been proven its efficiency in capt...
Recent advances in recommender systems have proved the potential of
Rein...
Interactive recommendation is able to learn from the interactive process...
Adversarial attacks, e.g., adversarial perturbations of the input and
ad...
Online recommendation requires handling rapidly changing user preference...
In light of the emergence of deep reinforcement learning (DRL) in recomm...
Recent advances in reinforcement learning have inspired increasing inter...
Deep reinforcement learning enables an agent to capture user's interest
...
Adversarial attacks pose significant challenges for detecting adversaria...
Interactive recommendation aims to learn from dynamic interactions betwe...
The novel coronavirus disease 2019 (COVID-19) has been spreading rapidly...
Deep learning algorithms have achieved excellent performance lately in a...
Synthesizing geometrical shapes from human brain activities is an intere...