46 citations · 78 across the 4 of their papers we have counts for
4 papers
MetaBalance: Improving Multi-Task Recommendations via Adapting Gradient Magnitudes of Auxiliary Tasks
Yun He, Xue Feng, Cheng Cheng +3
In many personalized recommendation scenarios, the generalization ability of a target task can be improved via learning with additional auxiliary tasks alongside this target task o…
Neuro-Symbolic Hierarchical Rule Induction
Claire Glanois, Xuening Feng, Zhaohui Jiang +4
We propose an efficient interpretable neuro-symbolic model to solve Inductive Logic Programming (ILP) problems. In this model, which is built from a set of meta-rules organised in…
Differentiable Logic Machines
Matthieu Zimmer, Xuening Feng, Claire Glanois +6
The integration of reasoning, learning, and decision-making is key to build more general artificial intelligence systems. As a step in this direction, we propose a novel neural-log…
Feature Interaction Interpretability: A Case for Explaining Ad-Recommendation Systems via Neural Interaction Detection
Michael Tsang, Dehua Cheng, Hanpeng Liu +3
Recommendation is a prevalent application of machine learning that affects many users; therefore, it is important for recommender models to be accurate and interpretable. In this w…