4 papers
Semantic Gaussian Mixture Variational Autoencoder for Sequential Recommendation
Beibei Li, Tao Xiang, Beihong Jin +2
Variational AutoEncoder (VAE) for Sequential Recommendation (SR), which learns a continuous distribution for each user-item interaction sequence rather than a determinate embedding…
An Unbiased Risk Estimator for Partial Label Learning with Augmented Classes
Jiayu Hu, Senlin Shu, Beibei Li +2
Partial Label Learning (PLL) is a typical weakly supervised learning task, which assumes each training instance is annotated with a set of candidate labels containing the ground-tr…
AsyCo: An Asymmetric Dual-task Co-training Model for Partial-label Learning
Beibei Li, Yiyuan Zheng, Beihong Jin +3
Partial-Label Learning (PLL) is a typical problem of weakly supervised learning, where each training instance is annotated with a set of candidate labels. Self-training PLL models…
Orthogonal Hyper-category Guided Multi-interest Elicitation for Micro-video Matching
Beibei Li, Beihong Jin, Yisong Yu +4
Watching micro-videos is becoming a part of public daily life. Usually, user watching behaviors are thought to be rooted in their multiple different interests. In the paper, we pro…