64 citations · 76 across the 5 of their papers we have counts for
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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…
cs.IR2020★ 2 cited
AutoRec: An Automated Recommender System
Ting-Hsiang Wang, Qingquan Song, Xiaotian Han +3
Realistic recommender systems are often required to adapt to ever-changing data and tasks or to explore different models systematically. To address the need, we present AutoRec, an…