271 citations · 460 across the 31 of their papers we have counts for
5 papers · 2 filters
AutoAttention: Automatic Field Pair Selection for Attention in User Behavior Modeling
Zuowu Zheng, Xiaofeng Gao, Junwei Pan +4
In Click-through rate (CTR) prediction models, a user's interest is usually represented as a fixed-length vector based on her history behaviors. Recently, several methods are propo…
On-Device Model Fine-Tuning with Label Correction in Recommender Systems
Yucheng Ding, Chaoyue Niu, Fan Wu +3
To meet the practical requirements of low latency, low cost, and good privacy in online intelligent services, more and more deep learning models are offloaded from the cloud to mob…
HIEN: Hierarchical Intention Embedding Network for Click-Through Rate Prediction
Zuowu Zheng, Changwang Zhang, Xiaofeng Gao +1
Click-through rate (CTR) prediction plays an important role in online advertising and recommendation systems, which aims at estimating the probability of a user clicking on a speci…
Trading Hard Negatives and True Negatives: A Debiased Contrastive Collaborative Filtering Approach
Chenxiao Yang, Qitian Wu, Jipeng Jin +3
Collaborative filtering (CF), as a standard method for recommendation with implicit feedback, tackles a semi-supervised learning problem where most interaction data are unobserved.…
Cross-Task Knowledge Distillation in Multi-Task Recommendation
Chenxiao Yang, Junwei Pan, Xiaofeng Gao +3
Multi-task learning (MTL) has been widely used in recommender systems, wherein predicting each type of user feedback on items (e.g, click, purchase) are treated as individual tasks…