no code implementations • 7 Feb 2024 • Ruichu Cai, Siyang Huang, Jie Qiao, Wei Chen, Yan Zeng, Keli Zhang, Fuchun Sun, Yang Yu, Zhifeng Hao
As a key component to intuitive cognition and reasoning solutions in human intelligence, causal knowledge provides great potential for reinforcement learning (RL) agents' interpretability towards decision-making by helping reduce the searching space.
3 code implementations • 6 Feb 2024 • Jun Wang, Wenjie Du, Wei Cao, Keli Zhang, Wenjia Wang, Yuxuan Liang, Qingsong Wen
In this paper, we conduct a comprehensive survey on the recently proposed deep learning imputation methods.
no code implementations • 16 Aug 2023 • Anpeng Wu, Haoxuan Li, Kun Kuang, Keli Zhang, Fei Wu
Learning directed acyclic graphs (DAGs) to identify causal relations underlying observational data is crucial but also poses significant challenges.
no code implementations • 25 Jun 2023 • Yuequn Liu, Ruichu Cai, Wei Chen, Jie Qiao, Yuguang Yan, Zijian Li, Keli Zhang, Zhifeng Hao
assumption is often violated due to the inherent dependencies among the event sequences.
no code implementations • 25 May 2023 • Yunze Tong, Junkun Yuan, Min Zhang, Didi Zhu, Keli Zhang, Fei Wu, Kun Kuang
With contrastive learning, we propose a learning potential-guided metric for domain heterogeneity by promoting learning variant features.
1 code implementation • 10 May 2023 • Jie Qiao, Ruichu Cai, Siyu Wu, Yu Xiang, Keli Zhang, Zhifeng Hao
Learning causal structure among event types from discrete-time event sequences is a particularly important but challenging task.
no code implementations • 7 May 2022 • Zijian Li, Ruichu Cai, Jiawei Chen, Yuguan Yan, Wei Chen, Keli Zhang, Junjian Ye
Based on this inspiration, we investigate the domain-invariant unweighted sparse associative structures and the domain-variant strengths of the structures.
2 code implementations • 30 Nov 2021 • Keli Zhang, Shengyu Zhu, Marcus Kalander, Ignavier Ng, Junjian Ye, Zhitang Chen, Lujia Pan
$\texttt{gCastle}$ is an end-to-end Python toolbox for causal structure learning.
no code implementations • 23 May 2021 • Ruichu Cai, Siyu Wu, Jie Qiao, Zhifeng Hao, Keli Zhang, Xi Zhang
We further propose a causal structure learning method on THP in a likelihood framework.
1 code implementation • 7 May 2021 • Keli Zhang, Marcus Kalander, Min Zhou, Xi Zhang, Junjian Ye
Alarm root cause analysis is a significant component in the day-to-day telecommunication network maintenance, and it is critical for efficient and accurate fault localization and failure recovery.
no code implementations • 22 Dec 2020 • Ruichu Cai, Jiawei Chen, Zijian Li, Wei Chen, Keli Zhang, Junjian Ye, Zhuozhang Li, Xiaoyan Yang, Zhenjie Zhang
To reduce the difficulty in the discovery of causal structure, we relax it to the sparse associative structure and propose a novel sparse associative structure alignment model for domain adaptation.
no code implementations • 4 Nov 2020 • Sitong Mao, Keli Zhang, Fu-Lai Chung
Under the settings of MSDA, different categories of the source dataset are not all collected from the same domain(s).
no code implementations • 28 Jun 2019 • Chunkai Zhang, Yingyang Chen, Ao Yin, Zhen Qin, Xing Zhang, Keli Zhang, Zoe L. Jiang
In this paper, we propose two new approaches for time series that utilize approximate trend feature information.