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Brain signal decoding is challenging because neural recordings are noisy and vary across individuals, while labeled data are often limited. Recent attention-based models on the symmetric positive definite (SPD) manifold have nevertheless achieved strong performance using covariance and connectivity representations, yet...
It is proved that the constrained decoupled objective is equivalent at optimality to a specific joint penalty on the inner and outer weights, for any positively homogeneous activation, and thus admits a clean projected and proximal formulation.
The Projected Koopman Operator Approximation framework for constructing Filtered EDMD operators is introduced, and under independent noiseless sampling and exact-rank identifiability, the resulting empirical operators converge almost surely to their population counterparts.
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