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arXiv AI By Md. Saiful Bari Siddiqui, Md Mohaiminul Islam, Md. Golam Rabiul Alam

DUA-D2C: Dynamic Uncertainty Aware Method for Overfitting Remediation in Deep Learning

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The paper introduces DUA-D2C, a Dynamic Uncertainty-Aware Divide2Conquer method that improves overfitting remediation in deep learning. It refines the traditional Divide2Conquer approach by dynamically weighting subset models based on a composite score of accuracy and normalized prediction entropy, allowing the central model to learn more from generalizable and confident edge models. The authors provide theoretical justification, show reduced model variance, and demonstrate significant generalization gains across image, audio, and text benchmarks, even when combined with standard regularizers like Dropout.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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