Browsing KINDI Center for Computing Research by Author "Hu, Minghui"
Now showing items 1-7 of 7
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Automated layer-wise solution for ensemble deep randomized feed-forward neural network
Hu, Minghui; Gao, Ruobin; Suganthan, Ponnuthurai N.; Tanveer, M. ( Elsevier B.V. , 2022 , Article)The randomized feed-forward neural network is a single hidden layer feed-forward neural network that enables efficient learning by optimizing only the output weights. The ensemble deep learning framework significantly ... -
Deep Reservoir Computing Based Random Vector Functional Link for Non-sequential Classification
Hu, Minghui; Gao, Ruobin; Suganthan, P. N. ( Institute of Electrical and Electronics Engineers Inc. , 2022 , Conference Paper)Reservoir Computing (RC) is well-suited for simpler sequential tasks which require inexpensive, rapid training, and the Echo State Network (ESN) plays a significant role in RC. In this article, we proposed variations of ... -
Ensemble deep learning: A review
Ganaie, M. A.; Hu, Minghui; Malik, A. K.; Tanveer, M.; Suganthan, P. N. ( Elsevier Ltd , 2022 , Other)Ensemble learning combines several individual models to obtain better generalization performance. Currently, deep learning architectures are showing better performance compared to the shallow or traditional models. Deep ... -
Experimental evaluation of stochastic configuration networks: Is SC algorithm inferior to hyper-parameter optimization method?
Hu, Minghui; Suganthan, P. N. ( Elsevier Ltd , 2022 , Article)To overcome the pitfalls of Random Vector Functional Link (RVFL), a network called Stochastic Configuration Networks (SCN) has been proposed. By constraining and adaptively selecting the range of randomized parameters using ... -
Representation learning using deep random vector functional link networks for clustering: Representation learning using deep RVFL for clustering
Hu, Minghui; Suganthan, P. N. ( Elsevier Ltd , 2022 , Article)Random Vector Functional Link (RVFL) Networks have received a lot of attention due to the fast training speed as the non-iterative solution characteristic. Currently, the main research direction of RVFLs has supervised ... -
Significant wave height forecasting using hybrid ensemble deep randomized networks with neurons pruning
Gao, Ruobin; Li, Ruilin; Hu, Minghui; Suganthan, Ponnuthurai Nagaratnam; Yuen, Kum Fai ( Elsevier Ltd , 2023 , Article)The reliable control of wave energy devices highly relies on the forecasts of wave heights. However, the dynamic characteristics and significant fluctuation of waves’ historical data pose challenges to precise predictions. ... -
Weighting and pruning based ensemble deep random vector functional link network for tabular data classification
Shi, Qiushi; Hu, Minghui; Suganthan, Ponnuthurai Nagaratnam; Katuwal, Rakesh ( Elsevier Ltd , 2022 , Article)In this paper, we first integrate normalization to the Ensemble Deep Random Vector Functional Link network (edRVFL). This re-normalization step can help the network avoid divergence of the hidden features. Then, we propose ...