Browsing KINDI Center for Computing Research by Author "Suganthan, P."
Now showing items 1-7 of 7
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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 ... -
Inpatient Discharges Forecasting for Singapore Hospitals by Machine Learning
Gao, Ruobin; Cheng, Wen Xin; Suganthan, P. N.; Yuen, Kum Fai ( Institute of Electrical and Electronics Engineers Inc. , 2022 , Article)Hospitals can predetermine the admission rate and facilitate resource allocation based on valid emergency requests and bed capacity estimation. The excess unoccupied beds can be determined with the help of forecasting the ... -
Minimum Variance Embedded Random Vector Functional Link Network with Privileged Information
Ganaie, M. A.; Tanveer, M.; Malik, A. K.; Suganthan, P. N. ( Institute of Electrical and Electronics Engineers Inc. , 2022 , Conference Paper)A teacher in a school plays significant role in classroom while teaching the students. Similarly, learning via privileged information (LUPI) gives extra information generated by a teacher to 'teach' the learning algorithm ... -
Oblique and rotation double random forest
Ganaie, M. A.; Tanveer, M.; Suganthan, P. N.; Snasel, V. ( Elsevier Ltd , 2022 , Article)Random Forest is an ensemble of decision trees based on the bagging and random subspace concepts. As suggested by Breiman, the strength of unstable learners and the diversity among them are the ensemble models’ core strength. ... -
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 ... -
Sample-Based Data Augmentation Based on Electroencephalogram Intrinsic Characteristics
Li, Ruilin; Wang, Lipo; Suganthan, P. N.; Sourina, Olga ( Institute of Electrical and Electronics Engineers Inc. , 2022 , Article)Deep learning for electroencephalogram-based classification is confronted with data scarcity, due to the time-consuming and expensive data collection procedure. Data augmentation has been shown as an effective way to improve ...