1 code implementation • 18 Dec 2023 • David Hason Rudd, Huan Huo, Guandong Xu
We propose the SMOGN-COREG model for semi-supervised regression, applying SMOGN to deal with unbalanced datasets and a nonparametric multi-learner co-regression (COREG) algorithm for labeling.
1 code implementation • Pacific-Asia Conference on Knowledge Discovery and Data Mining 2022 • David Hason Rudd, Huan Huo, Guandong Xu
We attempt to leverage the Mel spectrogram by decomposing distinguishable acoustic features for exploitation in our proposed architecture, which includes a novel feature map generator algorithm, a CNN-based network feature extractor and a multi-layer perceptron (MLP) classifier.
1 code implementation • Pacific-Asia Conference on Knowledge Discovery and Data Mining 2023 • David Hason Rudd, Huan Huo, Guandong Xu
Emotion recognition (ER) from speech signals is a robust approach since it cannot be imitated like facial expression or text based sentiment analysis.
Ranked #1 on Speech Emotion Recognition on EMODB (using extra training data)
no code implementations • 3 Dec 2023 • David Hason Rudd, Huan Huo, Md Rafiqul Islam, Guandong Xu
Our novel approach demonstrates a marked improvement in churn prediction, achieving a test accuracy of 91. 2%, a Mean Average Precision (MAP) score of 66, and a Macro-Averaged F1 score of 54 through the proposed hybrid fusion learning technique compared with late fusion and baseline models.
no code implementations • 23 Apr 2023 • David Hason Rudd, Huan Huo, Guandong Xu
Customer churn describes terminating a relationship with a business or reducing customer engagement over a specific period.
1 code implementation • International Conference on Digital Society and Intelligent Systems (DSInS) 2021 • David Hason Rudd, Huan Huo, Guandong Xu
Causal analysis of the churn model can predict whether a customer will churn in the foreseeable future and assist enterprises to identify effects and possible causes for churn and subsequently use that knowledge to apply tailored incentives.
no code implementations • 7 Apr 2023 • Yifan Yin, Xu Cheng, Fan Shi, Xiufeng Liu, Huan Huo, ShengYong Chen
Accurate and reliable optical remote sensing image-based small-ship detection is crucial for maritime surveillance systems, but existing methods often struggle with balancing detection performance and computational complexity.
1 code implementation • Human-Centric Intelligent Systems 2022 • David Hason Rudd, Huan Huo, Guandong Xu
We combine different algorithms including the SMOTE, ensemble ANN, and Bayesian networks to address churn prediction problems on a massive and high-dimensional finance data that is usually generated in financial institutions due to employing interval-based features used in Customer Relationship Management systems.
no code implementations • 16 Dec 2021 • Anchen Li, Bo Yang, Huan Huo, Farookh Hussain
In this paper, we propose a recommendation framework named Cayley-Dickson Recommender.
no code implementations • 7 Oct 2020 • Tao Zhang, Tianqing Zhu, Ping Xiong, Huan Huo, Zahir Tari, Wanlei Zhou
In this way, the impact of data correlation is relieved with the proposed feature selection scheme, and moreover, the privacy issue of data correlation in learning is guaranteed.
no code implementations • 27 Nov 2019 • Yang Li, Guodong Long, Tao Shen, Tianyi Zhou, Lina Yao, Huan Huo, Jing Jiang
Distantly supervised relation extraction intrinsically suffers from noisy labels due to the strong assumption of distant supervision.
1 code implementation • 4 Apr 2019 • Fengwen Chen, Shirui Pan, Jing Jiang, Huan Huo, Guodong Long
In this paper, we propose a novel framework called, dual attention graph convolutional networks (DAGCN) to address these problems.
Ranked #25 on Graph Classification on NCI1