19 citations · 23 across the 6 of their papers we have counts for
6 papers
MM-GEF: Multi-modal representation meet collaborative filtering
Hao Wu, Alejandro Ariza-Casabona, Bartłomiej Twardowski +1
In modern e-commerce, item content features in various modalities offer accurate yet comprehensive information to recommender systems. The majority of previous work either focuses…
PastNet: Introducing Physical Inductive Biases for Spatio-temporal Video Prediction
Hao Wu, Fan Xu, Chong Chen +3
In this paper, we investigate the challenge of spatio-temporal video prediction task, which involves generating future video frames based on historical spatio-temporal observation…
Do We Really Need Complicated Model Architectures For Temporal Networks?
Weilin Cong, Si Zhang, Jian Kang +5
Recurrent neural network (RNN) and self-attention mechanism (SAM) are the de facto methods to extract spatial-temporal information for temporal graph learning. Interestingly, we fo…
An ADMM-Incorporated Latent Factorization of Tensors Method for QoS Prediction
Jiajia Mi, Hao Wu
As the Internet developed rapidly, it is important to choose suitable web services from a wide range of candidates. Quality of service (QoS) describes the performance of a web serv…
Enhancing Spatiotemporal Prediction Model using Modular Design and Beyond
Haoyu Pan, Hao Wu, Tan Yang
Predictive learning uses a known state to generate a future state over a period of time. It is a challenging task to predict spatiotemporal sequence because the spatiotemporal sequ…
-Divergence-Based Latent Factorization of Tensors model for QoS prediction
Zemiao Peng, Hao Wu
A nonnegative latent factorization of tensors (NLFT) model can well model the temporal pattern hidden in nonnegative quality-of-service (QoS) data for predicting the unobserved one…