no code implementations • 10 Oct 2023 • Tong Yuan, Jian Yang, Zeyi Wen
With a concrete case study, our framework can derive a Bayesian Network from a dataset based on the causal relationships between weather and traffic events across the United States.
1 code implementation • 8 Dec 2022 • Jiantong Jiang, Zeyi Wen, Ajmal Mian
The mainstream BN structure learning methods require performing a large number of conditional independence (CI) tests.
1 code implementation • 8 Dec 2022 • Jiantong Jiang, Zeyi Wen, Atif Mansoor, Ajmal Mian
Bayesian networks (BNs) are attractive, because they are graphical and interpretable machine learning models.
no code implementations • 29 Sep 2021 • Yawen Chen, Zeyi Wen, Yile Chen, Jian Chen, Jin Huang
However, the recomputation of the Hessian matrix in the second-order optimization posts much extra computation and memory burden in the training.
no code implementations • 21 Nov 2019 • Zeyi Wen, Zeyu Huang, Rui Zhang
Entity extraction is an important task in text mining and natural language processing.
3 code implementations • 11 Nov 2019 • Qinbin Li, Zeyi Wen, Bingsheng He
There have been several recent studies on how to train GBDTs in the federated learning setting.
2 code implementations • 11 Nov 2019 • Qinbin Li, Zhaomin Wu, Zeyi Wen, Bingsheng He
Specifically, by investigating the property of gradient and the contribution of each tree in GBDTs, we propose to adaptively control the gradients of training data for each iteration and leaf node clipping in order to tighten the sensitivity bounds.
no code implementations • 8 Nov 2019 • Qinbin Li, Zeyi Wen, Bingsheng He
Our experimental results show that EFU often has 20\% higher hit ratio than LRU in the training with the Gaussian kernel.
1 code implementation • 23 Jul 2019 • Qinbin Li, Zeyi Wen, Zhaomin Wu, Sixu Hu, Naibo Wang, Yuan Li, Xu Liu, Bingsheng He
By systematically summarizing the existing federated learning systems, we present the design factors, case studies, and future research opportunities.
no code implementations • 23 Nov 2016 • Zeyi Wen, Bin Li, Rao Kotagiri, Jian Chen, Yawen Chen, Rui Zhang
The k-fold cross-validation is commonly used to evaluate the effectiveness of SVMs with the selected hyper-parameters.