64 citations · 90 across the 3 of their papers we have counts for
3 papers
cs.IR2020★ 64 cited
Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction
Qingquan Song, Dehua Cheng, Hanning Zhou +3
Click-Through Rate (CTR) prediction is one of the most important machine learning tasks in recommender systems, driving personalized experience for billions of consumers. Neural ar…
stat.ML2020★ 16 cited
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…
cs.DS2015★ 10 cited
Spectral Sparsification of Random-Walk Matrix Polynomials
Dehua Cheng, Yu Cheng, Yan Liu +2
We consider a fundamental algorithmic question in spectral graph theory: Compute a spectral sparsifier of random-walk matrix-polynomial whe…