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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Primitive sequences obtained from iterated antiderivatives of the CDF are homeomorphic to probability measures on compact intervals, equivalent to factorial-rescaled moments of the reflected variable, and yield sharp bounds on functionals when the first m terms are fixed.
Total variation between products of measures is at least a universal constant times that between the averaged measures' products.
QATS is a new polylog-time approximate decoding procedure for HMMs that builds admissible state sequences by locally maximizing likelihoods over paths with at most three segments via adaptive ternary segmentation and cumulative sum storage.
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.
Prospective Learning with Control proves ERM asymptotically achieves the Bayes optimal policy in non-stationary reset-free settings and outperforms time-aware RL on a 1D foraging benchmark.
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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.