no code implementations • 10 Mar 2022 • Ruijie Qi, Jianbin Huang, He Li, Qinglin Tan, Longji Huang, Jiangtao Cui
Moreover, we introduce the Update-To-Data (UTD) ratio to control the number of data reuses to improve the problem of low data utilization.
no code implementations • 8 Jan 2022 • Ling-Hao Chen, He Li, Wanyuan Zhang, Jianbin Huang, Xiaoke Ma, Jiangtao Cui, Ning li, Jaesoo Yoo
It remains a challenging task to jointly consider all different kinds of interactions and detect anomalous instances on multi-view attributed networks.
1 code implementation • 19 Nov 2021 • Yanni Li, Wenhui Zhang, Jiawei Liu, Xiaoli Kou, Hui Li, Jiangtao Cui
Despite the fact that deep neural networks (DNNs) have achieved prominent performance in various applications, it is well known that DNNs are vulnerable to adversarial examples/samples (AEs) with imperceptible perturbations in clean/original samples.
no code implementations • 19 Nov 2021 • Yanni Li, Bing Liu, Kaicheng Yao, Xiaoli Kou, Pengfan Lv, Yueshen Xu, Jiangtao Cui
what is the upper bound of the learningable tasks sequentially for a given CL method?
1 code implementation • 27 May 2020 • Yaming Yang, Ziyu Guan, Jian-Xin Li, Wei Zhao, Jiangtao Cui, Quan Wang
However, regarding Heterogeneous Information Network (HIN), existing HIN-oriented GCN methods still suffer from two deficiencies: (1) they cannot flexibly explore all possible meta-paths and extract the most useful ones for a target object, which hinders both effectiveness and interpretability; (2) they often need to generate intermediate meta-path based dense graphs, which leads to high computational complexity.
no code implementations • 18 Jun 2019 • Hui Li, Mengting Xu, Sourav S. Bhowmick, Changsheng Sun, Zhongyuan Jiang, Jiangtao Cui
As the number of required samples have been recently proven to be lower bounded by a particular threshold that presets tradeoff between the accuracy and efficiency, the result quality of these traditional solutions is hard to be further improved without sacrificing efficiency.