Matrix Orthogonalization Improves Memory in Recurrent Models
ai
According to a technical post by Ayush Tambde, applying matrix orthogonalization to recurrent neural networks improves memory capacity. Orthogonal matrices—arranged so their vectors are perpendicular to each other—appear to help these models retain information over time.
Source: https://ayushtambde.com/blog/matrix-orthogonalization-imp...
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