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FreIE Low-Frequency Spectral Bias in Neural Networks for Time-Series Tasks

Published in IEEE International Conference on Data Mining (ICDM), 2025

We demonstrate that spectral bias—the tendency of neural networks to fit low-frequency signals first—is a universal trait in time-series prediction, not an architectural artifact. To mitigate this, we propose FreLE, an algorithm using frequency regularization to improve model generalization. Extensive experiments confirm FreLE’s effectiveness.

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teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

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