no code implementations • CVPR 2022 • Ruoxi Shi, Xinyang Jiang, Caihua Shan, Yansen Wang, Dongsheng Li
Instead of looking at one format, it is a good solution to utilize the formats of VG and RG together to avoid these shortcomings.
1 code implementation • 15 May 2022 • Xiang Li, Renyu Zhu, Yao Cheng, Caihua Shan, Siqiang Luo, Dongsheng Li, Weining Qian
Further, for other homophilous nodes excluded in the neighborhood, they are ignored for information aggregation.
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no code implementations • 30 Mar 2022 • Shifu Yan, Caihua Shan, Wenyi Yang, Bixiong Xu, Dongsheng Li, Lili Qiu, Jie Tong, Qi Zhang
To this end, we propose a cross-metric multi-dimensional root cause analysis method, named CMMD, which consists of two key components: 1) relationship modeling, which utilizes graph neural network (GNN) to model the unknown complex calculation among metrics and aggregation function among dimensions from historical data; 2) root cause localization, which adopts the genetic algorithm to efficiently and effectively dive into the raw data and localize the abnormal dimension(s) once the KPI anomalies are detected.
no code implementations • NeurIPS 2021 • Caihua Shan, Yifei Shen, Yao Zhang, Xiang Li, Dongsheng Li
To address these issues, we propose a RL-enhanced GNN explainer, RG-Explainer, which consists of three main components: starting point selection, iterative graph generation and stopping criteria learning.
2 code implementations • NeurIPS 2021 • Xinyang Jiang, Lu Liu, Caihua Shan, Yifei Shen, Xuanyi Dong, Dongsheng Li
In this paper, we consider a different data format for images: vector graphics.
1 code implementation • 17 Aug 2021 • Yifei Shen, Yongji Wu, Yao Zhang, Caihua Shan, Jun Zhang, Khaled B. Letaief, Dongsheng Li
In this paper, we endeavor to obtain a better understanding of GCN-based CF methods via the lens of graph signal processing.
1 code implementation • 8 Jun 2020 • Xiang Li, Ben Kao, Caihua Shan, Dawei Yin, Martin Ester
We study the problem of applying spectral clustering to cluster multi-scale data, which is data whose clusters are of various sizes and densities.
no code implementations • 4 Nov 2019 • Caihua Shan, Nikos Mamoulis, Reynold Cheng, Guoliang Li, Xiang Li, Yuqiu Qian
In this paper, we propose a Deep Reinforcement Learning (RL) framework for task arrangement, which is a critical problem for the success of crowdsourcing platforms.
no code implementations • 4 Nov 2019 • Caihua Shan, Leong Hou U, Nikos Mamoulis, Reynold Cheng, Xiang Li
The number of microtasks depends on the budget allocated for the problem.