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Learning Subspace-Preserving Sparse Attention Graphs from Heterogeneous Multiview Data
SAGL learns subspace-preserving sparse attention graphs from heterogeneous multiview data via bilinear attention and dynamic sparsity gating, outperforming state-of-the-art unsupervised transfer learning methods.
Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026
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