activity
20192021
most citedLearning Graph Meta Embeddings for Cold-Start Ads in Click-Through Rate Prediction

49 citations · 104 across the 5 of their papers we have counts for

collaborators

5 papers

cs.IR202149 cited

Learning Graph Meta Embeddings for Cold-Start Ads in Click-Through Rate Prediction

Wentao Ouyang, Xiuwu Zhang, Shukui Ren +5

Click-through rate (CTR) prediction is one of the most central tasks in online advertising systems. Recent deep learning-based models that exploit feature embedding and high-order…

cs.IR20205 cited

MiNet: Mixed Interest Network for Cross-Domain Click-Through Rate Prediction

Wentao Ouyang, Xiuwu Zhang, Lei Zhao +5

Click-through rate (CTR) prediction is a critical task in online advertising systems. Existing works mainly address the single-domain CTR prediction problem and model aspects such…

cs.IR2019

Click-Through Rate Prediction with the User Memory Network

Wentao Ouyang, Xiuwu Zhang, Shukui Ren +3

Click-through rate (CTR) prediction is a critical task in online advertising systems. Models like Deep Neural Networks (DNNs) are simple but stateless. They consider each target ad…

cs.LG20192 cited

Representation Learning-Assisted Click-Through Rate Prediction

Wentao Ouyang, Xiuwu Zhang, Shukui Ren +3

Click-through rate (CTR) prediction is a critical task in online advertising systems. Most existing methods mainly model the feature-CTR relationship and suffer from the data spars…

cs.LG201948 cited

Deep Spatio-Temporal Neural Networks for Click-Through Rate Prediction

Wentao Ouyang, Xiuwu Zhang, Li Li +4

Click-through rate (CTR) prediction is a critical task in online advertising systems. A large body of research considers each ad independently, but ignores its relationship to othe…