AI Research
Uncertainty-Aware Ensemble Deep Randomized Neural Networks for Classification
Improving neural network robustness against noisy data using intuitionistic fuzzy logic.
The current state-of-the-art (SOTA) deep randomized neural networks, such as deep Random Vector Functional Link (dRVFL) and ensemble deep RVFL (edRVFL), treat all training samples uniformly, which limits their robustness and effectiveness when applied to real-world datasets conta...
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ArXiv CS.LG
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2 min
ArXiv CS.LG
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By integrating intuitionistic fuzzy logic, this research addresses the critical vulnerability of deep randomized neural networks to noise and outliers. This approach significantly enhances model reliability in real-world environments by intelligently weighting data based on local neighborhood characteristics.
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