arXiv:2606.16579v1 Announce Type: new Abstract: We extend the entropy formula of Menon and Yu for the real Deep Linear Network (DLN) to its complex and quaternionic analogues, obtaining a unified formula for DLNs over $\mathbb{R}$, $\mathbb{C}$, and $\mathbb{H}$.
This is a theoretical mathematics publication from arXiv, reflecting ongoing academic research in the field of deep learning theory.
For a strategic reader, this specific paper is not directly important as it is a highly specialized theoretical academic contribution, several layers removed from practical application or strategic impact.
No immediate or direct changes are brought about by this theoretical extension of an entropy formula, as it concerns foundational mathematical understanding rather than applied technology.
Refinement of mathematical understanding of deep linear networks.
Potential for future researchers to build upon this theoretical framework for more complex models.
Does not foreseeably impact AI development or strategic landscapes in the short to medium term.
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Read at arXiv cs.LG