232 citations · 684 across the 11 of their papers we have counts for
12 papers
Sequential Recommendation via Stochastic Self-Attention
Ziwei Fan, Zhiwei Liu, Alice Wang +4
Sequential recommendation models the dynamics of a user's previous behaviors in order to forecast the next item, and has drawn a lot of attention. Transformer-based approaches, whi…
Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformer
Ziwei Fan, Zhiwei Liu, Jiawei Zhang +3
In order to model the evolution of user preference, we should learn user/item embeddings based on time-ordered item purchasing sequences, which is defined as Sequential Recommendat…
Modeling Sequences as Distributions with Uncertainty for Sequential Recommendation
Ziwei Fan, Zhiwei Liu, Lei Zheng +2
The sequential patterns within the user interactions are pivotal for representing the user's preference and capturing latent relationships among items. The recent advancements of s…
JSCN: Joint Spectral Convolutional Network for Cross Domain Recommendation
Zhiwei Liu, Lei Zheng, Jiawei Zhang +2
Cross-domain recommendation can alleviate the data sparsity problem in recommender systems. To transfer the knowledge from one domain to another, one can either utilize the neighbo…
Semi-supervised Deep Representation Learning for Multi-View Problems
Vahid Noroozi, Sara Bahaadini, Lei Zheng +3
While neural networks for learning representation of multi-view data have been previously proposed as one of the state-of-the-art multi-view dimension reduction techniques, how to…
FI-GRL: Fast Inductive Graph Representation Learning via Projection-Cost Preservation
Fei Jiang, Lei Zheng, Jin Xu +1
Graph representation learning aims at transforming graph data into meaningful low-dimensional vectors to facilitate the employment of machine learning and data mining algorithms de…
Spectral Collaborative Filtering
Lei Zheng, Chun-Ta Lu, Fei Jiang +2
Despite the popularity of Collaborative Filtering (CF), CF-based methods are haunted by the \textit{cold-start} problem, which has a significantly negative impact on users' experie…
TI-CNN: Convolutional Neural Networks for Fake News Detection
Yang Yang, Lei Zheng, Jiawei Zhang +3
With the development of social networks, fake news for various commercial and political purposes has been appearing in large numbers and gotten widespread in the online world. With…
MARS: Memory Attention-Aware Recommender System
Lei Zheng, Chun-Ta Lu, Lifang He +4
In this paper, we study the problem of modeling users' diverse interests. Previous methods usually learn a fixed user representation, which has a limited ability to represent disti…
DeepMood: Modeling Mobile Phone Typing Dynamics for Mood Detection
Bokai Cao, Lei Zheng, Chenwei Zhang +6
The increasing use of electronic forms of communication presents new opportunities in the study of mental health, including the ability to investigate the manifestations of psychia…
SEVEN: Deep Semi-supervised Verification Networks
Vahid Noroozi, Lei Zheng, Sara Bahaadini +2
Verification determines whether two samples belong to the same class or not, and has important applications such as face and fingerprint verification, where thousands or millions o…
Joint Deep Modeling of Users and Items Using Reviews for Recommendation
Lei Zheng, Vahid Noroozi, Philip S. Yu
A large amount of information exists in reviews written by users. This source of information has been ignored by most of the current recommender systems while it can potentially al…