Kavli Affiliate: Yi Zhou | First 5 Authors: Xiyuan Chen, Xingyu Li, Yi Zhou, Tianming Yang, | Summary: Despite their outstanding performance in a broad spectrum of real-world tasks, deep artificial neural networks are sensitive to input noises, particularly adversarial perturbations. On the contrary, human and animal brains are much less vulnerable. In contrast to […]

Kavli Affiliate: Yi Zhou | First 5 Authors: Pengbo Hu, Xingyu Li, Yi Zhou, , | Summary: As deep learning advances, there is an ever-growing demand for models capable of synthesizing information from multi-modal resources to address the complex tasks raised from real-life applications. Recently, many large multi-modal datasets have been collected, on which researchers […]

Kavli Affiliate: Zheng Zhu | First 5 Authors: Kai Wang, Xiangyu Peng, Shuo Yang, Jianfei Yang, Zheng Zhu | Summary: Learning with noisy labels has aroused much research interest since data annotations, especially for large-scale datasets, may be inevitably imperfect. Recent approaches resort to a semi-supervised learning problem by dividing training samples into clean and […]

Kavli Affiliate: Zheng Zhu | First 5 Authors: Zheng Zhu, Meng Xu, Yining Di, Xiqun Chen, Jingru Yu | Summary: Matching and pickup processes are core features of ride-sourcing services. Previous studies have adopted abundant analytical models to depict the two processes and obtain operational insights; while the goodness of fit between models and data […]