Minimizing the sum of ℓ∞ norms enables separation of antisparse bounded sources via PCA followed by Givens rotations optimization, with claimed superior performance over prior methods in simulations.
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Sparse polynomial surrogates approximate parametric diffusion on community-structured graphs, with convergence guarantees via holomorphic regularity and tests on synthetic and real graphs.
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Exploring Bounded Component Analysis Using an $\ell_\infty$ Norm Criterion
Minimizing the sum of ℓ∞ norms enables separation of antisparse bounded sources via PCA followed by Givens rotations optimization, with claimed superior performance over prior methods in simulations.
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Surrogate models for diffusion on graphs via sparse polynomials
Sparse polynomial surrogates approximate parametric diffusion on community-structured graphs, with convergence guarantees via holomorphic regularity and tests on synthetic and real graphs.