Nov 14, 2018 · In this paper, we propose a Tree-structured Policy Gradient Recommendation (TPGR) framework, where a balanced hierarchical clustering tree is built over the ...
Abstract. Reinforcement learning (RL) has recently been introduced to interactive recommender systems (IRS) because of its nature.
Large-scale interactive recommendation with tree-structured policy gradient. AUTHORs: Haokun Chen. Haokun Chen. Shanghai Jiao Tong University. View Profile.
Apr 1, 2023 · To tackle these challenges, we propose a generic tree-structured RL framework taking both policy-based and value-based approaches into ...
The architecture of the Tree-structured Policy Gradient Recommendation (TPGR) is based on the constructed clustering tree. To ease the illustration, we assume ...
Recently, TPGR (tree-structured policy gradient for recommendation) [5] was proposed, which organized the policy into a tree structure and is efficient in both ...
The existing work that tries to deal with the large discrete action space problem by utilizing the deep deterministic policy gradient framework suffers from the ...
In this work, we propose Tree-structured Policy Gradient Recommendation (TPGR) framework to achieve high efficiency as well as high effectiveness.
... Recommendation System and CTR Prediction - DeepRec-1/RL/Extend/[AAAI 19][Huawei] Large-scale Interactive Recommendation with Tree-structured Policy Gradient.
We derive the natural policy gradient method for formal grammars and evaluate the method on several tasks. Together, the individual ...