A Riemannian L-BFGS method with adapted Cauchy-point bound handling outperforms classical interior-point and L-BFGS-B solvers on mixed manifold-plus-bounds problems by orders of magnitude.
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EEG-MoCE assigns each modality to a learnable-curvature hyperbolic expert and applies curvature-aware fusion to achieve state-of-the-art results on emotion recognition, sleep staging, and cognitive assessment benchmarks.
citing papers explorer
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A Riemannian quasi-Newton algorithm for optimization with Euclidean bounds
A Riemannian L-BFGS method with adapted Cauchy-point bound handling outperforms classical interior-point and L-BFGS-B solvers on mixed manifold-plus-bounds problems by orders of magnitude.
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EEG-Based Multimodal Learning via Hyperbolic Mixture-of-Curvature Experts
EEG-MoCE assigns each modality to a learnable-curvature hyperbolic expert and applies curvature-aware fusion to achieve state-of-the-art results on emotion recognition, sleep staging, and cognitive assessment benchmarks.