Connectionists: ICONIP 2020 SS on "Randomization-based learning Algorithms and applications"

[Ponnuthurai Nagaratnam Suganthan]

Dear  Colleague,



We look forward to your participation in the "Randomization-Based Learning Algorithms and Their Applications"  Special Session at ICONIP 2020 in Bangkok, Thailand during 18-22 November. Online presentation is possible/encouraged. Topics of interests are listed below. Please feel free to forward to your collaborators.



Please email your intention to submit to    epnsugan at ntu.edu.sg<mailto:epnsugan at ntu.edu.sg>

More details from:  https://www.apnns.org/ICONIP2020/



Topics of interests include random vector functional link (RVFL), echo state networks (ESN), liquid state networks (LSN), kernel ridge regression (KRR) with randomization, extreme learning machines (ELM), random forests (RF),  Randomized convolutional neural networks, Randomized internal representation learning, Regression, classification and time series analysis by randomization-based methods, Kernel methods (kernel ridge regression, kernel adaptive filters) with randomization, Feedforward, recurrent, multilayer, deep and other structures with randomization, Ensemble learning with randomization,  Moore-Penrose pseudo inverse, SVD and other solution procedures, Gaussian process regression, Randomization-based methods for large-scale problems with and without kernels, Theoretical analysis of randomization-based methods, Comparative studies with competing methods with or without randomization, Applications of randomized methods in domains such as power systems, biomedical, finance, signal processing, big data and all other relevant areas and so on.





Thank you

Suganthan

https://www.ntu.edu.sg/home/epnsugan

    https://github.com/P-N-Suganthan





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