219 citations · 862 across the 18 of their papers we have counts for
11 papers · 1 filter
Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Network
Xiyue Zhang, Chao Huang, Yong Xu +5
Accurate forecasting of citywide traffic flow has been playing critical role in a variety of spatial-temporal mining applications, such as intelligent traffic control and public ri…
Multiplex Behavioral Relation Learning for Recommendation via Memory Augmented Transformer Network
Lianghao Xia, Chao Huang, Yong Xu +3
Capturing users' precise preferences is of great importance in various recommender systems (eg., e-commerce platforms), which is the basis of how to present personalized interestin…
Knowledge-Enhanced Hierarchical Graph Transformer Network for Multi-Behavior Recommendation
Lianghao Xia, Chao Huang, Yong Xu +5
Accurate user and item embedding learning is crucial for modern recommender systems. However, most existing recommendation techniques have thus far focused on modeling users' prefe…
Graph-Enhanced Multi-Task Learning of Multi-Level Transition Dynamics for Session-based Recommendation
Chao Huang, Jiahui Chen, Lianghao Xia +6
Session-based recommendation plays a central role in a wide spectrum of online applications, ranging from e-commerce to online advertising services. However, the majority of existi…
Knowledge-aware Coupled Graph Neural Network for Social Recommendation
Chao Huang, Huance Xu, Yong Xu +7
Social recommendation task aims to predict users' preferences over items with the incorporation of social connections among users, so as to alleviate the sparse issue of collaborat…
Graph Meta Network for Multi-Behavior Recommendation
Lianghao Xia, Yong Xu, Chao Huang +2
Modern recommender systems often embed users and items into low-dimensional latent representations, based on their observed interactions. In practical recommendation scenarios, use…
Social Recommendation with Self-Supervised Metagraph Informax Network
Xiaoling Long, Chao Huang, Yong Xu +4
In recent years, researchers attempt to utilize online social information to alleviate data sparsity for collaborative filtering, based on the rationale that social networks offers…
Boosting the Generalization Capability in Cross-Domain Few-shot Learning via Noise-enhanced Supervised Autoencoder
Hanwen Liang, Qiong Zhang, Peng Dai +1
State of the art (SOTA) few-shot learning (FSL) methods suffer significant performance drop in the presence of domain differences between source and target datasets. The strong dis…
Class Semantics-based Attention for Action Detection
Deepak Sridhar, Niamul Quader, Srikanth Muralidharan +3
Action localization networks are often structured as a feature encoder sub-network and a localization sub-network, where the feature encoder learns to transform an input video to f…
Fedlearn-Algo: A flexible open-source privacy-preserving machine learning platform
Bo Liu, Chaowei Tan, Jiazhou Wang +7
In this paper, we present Fedlearn-Algo, an open-source privacy preserving machine learning platform. We use this platform to demonstrate our research and development results on pr…
Learning a Proposal Classifier for Multiple Object Tracking
Peng Dai, Renliang Weng, Wongun Choi +3
The recent trend in multiple object tracking (MOT) is heading towards leveraging deep learning to boost the tracking performance. However, it is not trivial to solve the data-assoc…