Convex surrogates derived via concentration inequalities replace the Poincaré loss J(g) for nonlinear dimension reduction, delivering suboptimality bounds for polynomials and empirical gains over iterative minimization on benchmarks.
Alexandre-pasco/tensap: V1.6.2-poincare- learning-paper
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Surrogate to Poincar\'e inequalities on manifolds for dimension reduction in nonlinear feature spaces
Convex surrogates derived via concentration inequalities replace the Poincaré loss J(g) for nonlinear dimension reduction, delivering suboptimality bounds for polynomials and empirical gains over iterative minimization on benchmarks.