14 citations · 36 across the 8 of their papers we have counts for
8 papers
Influence-aware Task Assignment in Spatial Crowdsourcing (Technical Report)
Xuanhao Chen, Yan Zhao, Kai Zheng +2
With the widespread diffusion of smartphones, Spatial Crowdsourcing (SC), which aims to assign spatial tasks to mobile workers, has drawn increasing attention in both academia and…
HIFI: Anomaly Detection for Multivariate Time Series with High-order Feature Interactions
Liwei Deng, Xuanhao Chen, Yan Zhao +1
Monitoring complex systems results in massive multivariate time series data, and anomaly detection of these data is very important to maintain the normal operation of the systems.…
Hierarchical Hyperedge Embedding-based Representation Learning for Group Recommendation
Lei Guo, Hongzhi Yin, Tong Chen +2
In this work, we study group recommendation in a particular scenario, namely Occasional Group Recommendation (OGR). Most existing works have addressed OGR by aggregating group memb…
Overcoming Data Sparsity in Group Recommendation
Hongzhi Yin, Qinyong Wang, Kai Zheng +2
It has been an important task for recommender systems to suggest satisfying activities to a group of users in people's daily social life. The major challenge in this task is how to…
SOUP: Spatial-Temporal Demand Forecasting and Competitive Supply
Bolong Zheng, Qi Hu, Lingfeng Ming +4
We consider a setting with an evolving set of requests for transportation from an origin to a destination before a deadline and a set of agents capable of servicing the requests. I…
Reconstruction Regularized Deep Metric Learning for Multi-label Image Classification
Changsheng Li, Chong Liu, Lixin Duan +2
In this paper, we present a novel deep metric learning method to tackle the multi-label image classification problem. In order to better learn the correlations among images feature…
Bilinear Graph Neural Network with Neighbor Interactions
Hongmin Zhu, Fuli Feng, Xiangnan He +4
Graph Neural Network (GNN) is a powerful model to learn representations and make predictions on graph data. Existing efforts on GNN have largely defined the graph convolution as a…
Learning Transferable Self-attentive Representations for Action Recognition in Untrimmed Videos with Weak Supervision
Xiao-Yu Zhang, Haichao Shi, Changsheng Li +3
Action recognition in videos has attracted a lot of attention in the past decade. In order to learn robust models, previous methods usually assume videos are trimmed as short seque…