Monitoring Primitive Interactions During the Training of DNNs Article Swipe

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Jie Ren , Xinhao Zheng , Jiyu Liu , Andrew Lizarraga , Ying Wu , Liang Lin , Quanshi Zhang ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.1609/aaai.v39i19.34223

This paper focuses on the newly emerged research topic, i.e., whether the complex decision-making logic of a DNN can be mathematically summarized into a few simple logics. Beyond the explanation of a static DNN, in this paper, we hope to show that the seemingly complex learning dynamics of a DNN can be faithfully represented as the change of a few primitive interaction patterns encoded by the DNN. Therefore, we redefine the interaction of principal feature components in intermediate-layer features, which enables us to concisely summarize the highly complex dynamics of interactions throughout the learning of the DNN. The mathematical faithfulness of the new interaction is experimentally verified. From the perspective of learning efficiency, we find that the interactions naturally belong to five groups (reliable, withdrawn, forgotten, betraying, and fluctuating interactions), each representing a distinct type of dynamics of an interaction being learned and/or being forgotten. This provides deep insights into the learning process of a DNN.

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Training (meteorology) Psychology Computer science Biology Geography Meteorology

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Type: article
Language: en
Landing Page: https://doi.org/10.1609/aaai.v39i19.34223
PDF: https://ojs.aaai.org/index.php/AAAI/article/download/34223/36378
OA Status: diamond
Cited By: 1
Related Works: 10
OpenAlex ID: https://openalex.org/W4409363629

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OpenAlex ID: https://openalex.org/W4409363629

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DOI: https://doi.org/10.1609/aaai.v39i19.34223

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Title: Monitoring Primitive Interactions During the Training of DNNs

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Type: article

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Language: en

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Publication year: 2025

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Publication date: 2025-04-11

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Authors: Jie Ren, Xinhao Zheng, Jiyu Liu, Andrew Lizarraga, Ying Wu, Liang Lin, Quanshi Zhang

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Landing page: https://doi.org/10.1609/aaai.v39i19.34223

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OA URL: https://ojs.aaai.org/index.php/AAAI/article/download/34223/36378

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Concepts: Training (meteorology), Psychology, Computer science, Biology, Geography, Meteorology

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Cited by: 1

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Citations by year (recent): 2024: 1

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