9 citations · 14 across the 15 of their papers we have counts for
7 papers · 1 filter
JDRec: Practical Actor-Critic Framework for Online Combinatorial Recommender System
Xin Zhao, Zhiwei Fang, Yuchen Guo +3
A combinatorial recommender (CR) system feeds a list of items to a user at a time in the result page, in which the user behavior is affected by both contextual information and item…
NDGGNET-A Node Independent Gate based Graph Neural Networks
Ye Tang, Xuesong Yang, Xinrui Liu +3
Graph Neural Networks (GNNs) is an architecture for structural data, and has been adopted in a mass of tasks and achieved fabulous results, such as link prediction, node classifica…
Gating-adapted Wavelet Multiresolution Analysis for Exposure Sequence Modeling in CTR prediction
Xiaoxiao Xu, Zhiwei Fang, Qian Yu +7
The exposure sequence is being actively studied for user interest modeling in Click-Through Rate (CTR) prediction. However, the existing methods for exposure sequence modeling brin…
On the Adaptation to Concept Drift for CTR Prediction
Congcong Liu, Yuejiang Li, Fei Teng +5
Click-through rate (CTR) prediction is a crucial task in web search, recommender systems, and online advertisement displaying. In practical application, CTR models often serve with…
IA-GCN: Interactive Graph Convolutional Network for Recommendation
Yinan Zhang, Pei Wang, Congcong Liu +7
Recently, Graph Convolutional Network (GCN) has become a novel state-of-art for Collaborative Filtering (CF) based Recommender Systems (RS). It is a common practice to learn inform…
Rethinking Position Bias Modeling with Knowledge Distillation for CTR Prediction
Congcong Liu, Yuejiang Li, Jian Zhu +4
Click-through rate (CTR) Prediction is of great importance in real-world online ads systems. One challenge for the CTR prediction task is to capture the real interest of users from…
Alleviating Cold-start Problem in CTR Prediction with A Variational Embedding Learning Framework
Xiaoxiao Xu, Chen Yang, Qian Yu +7
We propose a general Variational Embedding Learning Framework (VELF) for alleviating the severe cold-start problem in CTR prediction. VELF addresses the cold start problem via alle…