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ENTITY Cascading Through the Hierarchy: Regularizer-Induced Feature Detection as Phase Transitions in Deep Linear Neural Networks

Cascading Through the Hierarchy: Regularizer-Induced Feature Detection as Phase Transitions in Deep Linear Neural Networks

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    Deep Learning Theory Connects Feature Detection to Phase Transitions

    Researchers have developed a theoretical framework for deep learning, drawing parallels with statistical physics. By treating regularization strength as an external parameter, they identified a cascade of phase transiti…