Translated data: The Amazon research team has proposed an innovative approach using deep learning to optimize the performance of neural networks in processing complex tabular data. This method enhances the network's ability to parse heterogeneous tabular data by transforming table features into low-frequency representations. Experiments have shown that it outperforms conventional data processing methods in improving network performance and computational efficiency. This research provides new insights and promising methods for enhancing neural networks' capabilities in handling complex tabular data.