SA-PAL combines adaptive timesteps and position-dependent friction in Langevin dynamics, reporting 1.5-3x faster mixing on Rosenbrock and Mueller-Brown potentials plus order-of-magnitude efficiency gains on other test problems.
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Direct fixed-weight solver for free-support Wasserstein medians relocates atoms using OT barycentric projections and inverse-distance weights, achieving monotone descent on smoothed objectives with fewer subproblems than nested Weiszfeld baselines.
Proposes a scale-calibrated median-of-means estimator for robust aggregation of distributed PCA estimates on the product of Euclidean space and Grassmann manifold.
Joint location-scale minimization for geometric medians on product manifolds degenerates to marginal medians, and three new scale-selection methods restore identifiability with asymptotic guarantees.
citing papers explorer
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Accelerated sampling using SamAdams variable timesteps and position-adaptive Langevin dynamics
SA-PAL combines adaptive timesteps and position-dependent friction in Langevin dynamics, reporting 1.5-3x faster mixing on Rosenbrock and Mueller-Brown potentials plus order-of-magnitude efficiency gains on other test problems.
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Fast Computation of Free-Support Wasserstein Medians
Direct fixed-weight solver for free-support Wasserstein medians relocates atoms using OT barycentric projections and inverse-distance weights, achieving monotone descent on smoothed objectives with fewer subproblems than nested Weiszfeld baselines.
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Scale-Calibrated Median-of-Means for Robust Distributed Principal Component Analysis
Proposes a scale-calibrated median-of-means estimator for robust aggregation of distributed PCA estimates on the product of Euclidean space and Grassmann manifold.
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Scale selection for geometric medians on product manifolds
Joint location-scale minimization for geometric medians on product manifolds degenerates to marginal medians, and three new scale-selection methods restore identifiability with asymptotic guarantees.