17 citations · 25 across the 5 of their papers we have counts for
5 papers
An Interpretable Alternative to Neural Representation Learning for Rating Prediction -- Transparent Latent Class Modeling of User Reviews
Giuseppe Serra, Peter Tino, Zhao Xu +1
Nowadays, neural network (NN) and deep learning (DL) techniques are widely adopted in many applications, including recommender systems. Given the sparse and stochastic nature of co…
Entire Space Cascade Delayed Feedback Modeling for Effective Conversion Rate Prediction
Yunfeng Zhao, Xu Yan, Xiaoqiang Gui +6
Conversion rate (CVR) prediction is an essential task for large-scale e-commerce platforms. However, refund behaviors frequently occur after conversion in online shopping systems,…
Learning Sparsity of Representations with Discrete Latent Variables
Zhao Xu, Daniel Onoro Rubio, Giuseppe Serra +1
Deep latent generative models have attracted increasing attention due to the capacity of combining the strengths of deep learning and probabilistic models in an elegant way. The da…
Self-Supervised Representation Learning via Latent Graph Prediction
Yaochen Xie, Zhao Xu, Shuiwang Ji
Self-supervised learning (SSL) of graph neural networks is emerging as a promising way of leveraging unlabeled data. Currently, most methods are based on contrastive learning adapt…
Infinite Hidden Relational Models
Zhao Xu, Volker Tresp, Kai Yu +1
In many cases it makes sense to model a relationship symmetrically, not implying any particular directionality. Consider the classical example of a recommendation system where the…