no code implementations • CVPR 2023 • Chuanwen Feng, Yilong Ren, Xike Xie
Learning with noisy labels is challenging because the performance of the deep neural networks (DNN) drastically degenerates, due to confirmation bias caused by the network memorization over noisy labels.
no code implementations • 7 Dec 2022 • Yukun Cao, Xike Xie, Kexin Huang
The process of data exploration can be viewed as the process of training a classifier, which determines whether a database tuple is interesting to a user.
no code implementations • 9 Feb 2021 • Zhengyang Zhou, Yang Wang, Xike Xie, Lei Qiao, Yuantao Li
The high dynamics and heterogeneous interactions in the complicated urban systems have raised the issue of uncertainty quantification in spatiotemporal human mobility, to support critical decision-makings in risk-aware web applications such as urban event prediction where fluctuations are of significant interests.
1 code implementation • 16 Jul 2020 • Yu Hao, Xin Cao, Yixiang Fang, Xike Xie, Sibo Wang
In attributed graphs, both the structure and attribute information can be utilized for link prediction.
no code implementations • 19 Feb 2020 • Zhengyang Zhou, Yang Wang, Xike Xie, Lianliang Chen, Hengchang Liu
Real-time traffic accident forecasting is increasingly important for public safety and urban management (e. g., real-time safe route planning and emergency response deployment).