A dynamic product-level factor model with Bayesian variational inference improves predictive accuracy for consumer demand in high-dimensional retail settings by capturing inertia and correlated heterogeneity.
Econometrica , volume =
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The Bellman operator admits an exact block-diagonal decomposition under localized interaction structures, enabling scalable structural estimation of replacement decisions across 14,344 GPU nodes.
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Dynamic Consumer Demand at Large Scale
A dynamic product-level factor model with Bayesian variational inference improves predictive accuracy for consumer demand in high-dimensional retail settings by capturing inertia and correlated heterogeneity.
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Scalable Structural Estimation of Networked Infrastructure: Exact Decomposition for Localized Coordination
The Bellman operator admits an exact block-diagonal decomposition under localized interaction structures, enabling scalable structural estimation of replacement decisions across 14,344 GPU nodes.