Approximate stochastic localization plus conductance transfers yield a weak Poincaré inequality for the SK model at β < 1/2, enabling efficient Glauber sampling from a warm start.
Introduction to the SK model
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This is a review paper for the "Current Developments in Mathematics 2014" conference.
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Presents the first iterative spectral algorithm for near-optimal solutions to random quadratic optimization over the hypercube, resolving Subag's conjecture via potential Hessian ascent and SDE approximation.
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Weak Poincar\'e Inequalities via Approximate Stochastic Localization: Application to Sampling the Sherrington-Kirkpatrick Model
Approximate stochastic localization plus conductance transfers yield a weak Poincaré inequality for the SK model at β < 1/2, enabling efficient Glauber sampling from a warm start.
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Potential Hessian Ascent: The Sherrington-Kirkpatrick Model
Presents the first iterative spectral algorithm for near-optimal solutions to random quadratic optimization over the hypercube, resolving Subag's conjecture via potential Hessian ascent and SDE approximation.