Frame Theoretical Derivation of Three Factor Learning Rule for Oja's Subspace Rule

Taiki Yamada

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arXiv · 2604.02849

Frame Theoretical Derivation of Three Factor Learning Rule for Oja's Subspace Rule

Taiki Yamada

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Abstract

We show that the error-gated Hebbian rule for PCA (EGHR-PCA), a three-factor learning rule equivalent to Oja's subspace rule under Gaussian inputs, can be systematically derived from Oja's subspace rule using frame theory. The global third factor in EGHR-PCA arises exactly as a frame coefficient when the learning rule is expanded with respect to a natural frame on the space of symmetric matrices. This provides a principled, non-heuristic derivation of a biologically plausible learning rule from its mathematically canonical counterpart.

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Taiki Yamada. 2026-04-03. Frame Theoretical Derivation of Three Factor Learning Rule for Oja's Subspace Rule. https://arxiv.org/abs/2604.02849

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