A one-to-one correspondence maps maximal LDP channels under the Blackwell order to vertices of a finite-dimensional polytope, making optimal privacy-utility trade-offs computable via linear programming or vertex enumeration for general problems.
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On Optimum Recognition Error and Reject Tradeoff
7 Pith papers cite this work, alongside 3,769 external citations. Polarity classification is still indexing.
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UNVERDICTED 7representative citing papers
Bayes-THIS applies sparse Bayesian regression with automatic relevance determination to infer hypergraph structure from dynamical data and proves that Taylor expansions create indistinguishable spurious pairwise terms when higher-order interactions concentrate on nodes lacking lower-order links.
A bias-reduced Bayesian optimal experimental design procedure using Kullback-Leibler divergence is shown to select high-value steel mass-flow observations that reduce network-structure uncertainty in a U.S. steel MFA, with the optimum depending on total data budget.
A Bayesian framework learns uncertainties from data to generate robust multi-topology express network designs that reduce tail delivery risks at modest extra cost in simulations.
Survey and experiment with 606 analysts show regularization adoption depends on usability and community norms, not formal recommendations.
Using distribution regression on Consumption Expenditure Interview Survey data, the study decomposes the 2018-2022 decline in consumption inequality into contributions from conditional consumption distributions, rising asset holdings, and household characteristics for male-headed households.
Support sufficiency is a dynamic compression criterion regulated by consequence geometry and resource constraints, with simulations showing adaptive controllers outperform fixed-resolution ones in cumulative utility.
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Optimal Privacy-Utility Trade-Offs in LDP: Functional and Geometric Perspectives
A one-to-one correspondence maps maximal LDP channels under the Blackwell order to vertices of a finite-dimensional polytope, making optimal privacy-utility trade-offs computable via linear programming or vertex enumeration for general problems.
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Bayesian hypergraph inference from scarce and noisy dynamical observations
Bayes-THIS applies sparse Bayesian regression with automatic relevance determination to infer hypergraph structure from dynamical data and proves that Taylor expansions create indistinguishable spurious pairwise terms when higher-order interactions concentrate on nodes lacking lower-order links.
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Intelligent data collection for network discrimination in material flow analysis using Bayesian optimal experimental design
A bias-reduced Bayesian optimal experimental design procedure using Kullback-Leibler divergence is shown to select high-value steel mass-flow observations that reduce network-structure uncertainty in a U.S. steel MFA, with the optimum depending on total data budget.
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Bayesian Multi-Topology Express Transportation Network Design under Posterior Predictive Demand, Sorting-Efficiency and Delivery-Time Uncertainty
A Bayesian framework learns uncertainties from data to generate robust multi-topology express network designs that reduce tail delivery risks at modest extra cost in simulations.
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Why is Regularization Underused? An Empirical Study on Trust and Adoption of Statistical Methods
Survey and experiment with 606 analysts show regularization adoption depends on usability and community norms, not formal recommendations.
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Distributional Decomposition of Consumption Inequality Change During COVID-19
Using distribution regression on Consumption Expenditure Interview Survey data, the study decomposes the 2018-2022 decline in consumption inequality into contributions from conditional consumption distributions, rising asset holdings, and household characteristics for male-headed households.
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Support Sufficiency as Consequence-Sensitive Compression in Belief Arbitration
Support sufficiency is a dynamic compression criterion regulated by consequence geometry and resource constraints, with simulations showing adaptive controllers outperform fixed-resolution ones in cumulative utility.