no code implementations • 20 Jul 2023 • Manqing Dong, Zhanxiang Zhao, Yitong Geng, Wentao Li, Wei Wang, Huai Jiang
Time series anomaly detection is crucial for industrial monitoring services that handle a large volume of data, aiming to ensure reliability and optimize system performance.
no code implementations • EMNLP 2021 • Manqing Dong, Chunguang Pan, Zhipeng Luo
Neural relation extraction models have shown promising results in recent years; however, the model performance drops dramatically given only a few training samples.
1 code implementation • 9 Sep 2021 • Zhipeng Luo, Zhixing He, Jin Wang, Manqing Dong, Jianqiang Huang, Mingjian Chen, Bohang Zheng
Temporal relational data, perhaps the most commonly used data type in industrial machine learning applications, needs labor-intensive feature engineering and data analyzing for giving precise model predictions.
no code implementations • 1 Jan 2021 • Manqing Dong, Lina Yao, Xianzhi Wang, Xiwei Xu, Liming Zhu
A key challenge for meta-optimization based approaches is to determine whether an initialization condition can be generalized to tasks with diverse distributions to accelerate learning.
1 code implementation • 7 Jul 2020 • Manqing Dong, Feng Yuan, Lina Yao, Xiwei Xu, Liming Zhu
However, most meta-learning based recommendation approaches adopt model-agnostic meta-learning for parameter initialization, where the global sharing parameter may lead the model into local optima for some users.
no code implementations • 8 Apr 2020 • Manqing Dong, Feng Yuan, Lina Yao, Xianzhi Wang, Xiwei Xu, Liming Zhu
A significant remaining challenge for existing recommender systems is that users may not trust the recommender systems for either lack of explanation or inaccurate recommendation results.
1 code implementation • 18 Sep 2019 • Xiang Zhang, Lina Yao, Manqing Dong, Zhe Liu, Yu Zhang, Yong Li
Furthermore, to enhance the explainability, we develop an attention mechanism to automatically learn the importance of each EEG channels in the seizure diagnosis procedure.
2 code implementations • 31 Jul 2019 • Xiang Zhang, Xiaocong Chen, Manqing Dong, Huan Liu, Chang Ge, Lina Yao
In light of this, we propose a novel multi-task generative adversarial network to convert the individual's EEG signals evoked by geometrical shapes to the original geometry.
1 code implementation • 31 Jul 2019 • Xiang Zhang, Xiaocong Chen, Lina Yao, Chang Ge, Manqing Dong
Deep learning algorithms have achieved excellent performance lately in a wide range of fields (e. g., computer version).
no code implementations • 21 Jun 2018 • Manqing Dong, Lina Yao, Xianzhi Wang, Boualem Benatallah, Shuai Zhang
We develop a gradient boost module and embed it into the proposed convolutional autoencoder with neural decision forest to improve the performance.
no code implementations • 9 May 2018 • Manqing Dong, Lina Yao, Xianzhi Wang, Boualem Benatallah, Chaoran Huang, Xiaodong Ning
Online reviews play an important role in influencing buyers' daily purchase decisions.
no code implementations • 8 May 2018 • Shuai Zhang, Lina Yao, Aixin Sun, Sen Wang, Guodong Long, Manqing Dong
Modeling user-item interaction patterns is an important task for personalized recommendations.