GREASE: Generate Factual and Counterfactual Explanations for GNN-based Recommendations

no code implementations • 4 Aug 2022 • Ziheng Chen, Fabrizio Silvestri, Jia Wang, Yongfeng Zhang, Zhenhua Huang, Hongshik Ahn, Gabriele Tolomei

Although powerful, it is very difficult for a GNN-based recommender system to attach tangible explanations of why a specific item ends up in the list of suggestions for a given user.

counterfactual Graph Classification +1

Automatic Curriculum Learning With Over-repetition Penalty for Dialogue Policy Learning

no code implementations • 28 Dec 2020 • Yangyang Zhao, Zhenyu Wang, Zhenhua Huang

We propose a novel framework, Automatic Curriculum Learning-based Deep Q-Network (ACL-DQN), which replaces the traditional random sampling method with a teacher policy model to realize the dialogue policy for automatic curriculum learning.

EdgeCNN: Convolutional Neural Network Classification Model with small inputs for Edge Computing

1 code implementation • 30 Sep 2019 • Shunzhi Yang, Zheng Gong, Kai Ye, Yungen Wei, Zheng Huang, Zhenhua Huang

Therefore, a small input network can be designed to reduce computation.

Edge-computing Efficient Neural Network +1