Derives near-optimal nonasymptotic excess-risk bounds for Engression and reverse Markov Engression over Hölder classes via energy distance.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Proves graphical convergence of empirical subdifferentials for sampled OT objectives to the population subdifferential, ensuring subgradient methods approach stationary points of the true problem.
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Theoretical Analysis of Engression and Reverse Markov Engression
Derives near-optimal nonasymptotic excess-risk bounds for Engression and reverse Markov Engression over Hölder classes via energy distance.
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Convergence of empirical subgradients for optimal transport-based objectives
Proves graphical convergence of empirical subdifferentials for sampled OT objectives to the population subdifferential, ensuring subgradient methods approach stationary points of the true problem.