Extends UMVUE theory to Bregman losses by introducing dual-space unbiasedness and proving Rao-Blackwell and Lehmann-Scheffé analogs for type-I Bregman UMVUEs.
USSR Computa- tional Mathematics And Mathematical Physics6, 1–50 (1966), https://www
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KFBI-ADI schemes achieve second-order accuracy and unconditional stability for 3D heat equations with irregular boundaries and interfaces, verified numerically and applied to Stefan problems with level sets.
A mixed-integer convex formulation for graph isomorphism is solved via first-order methods and variable fixing, outperforming integer feasibility on 6 of 12 graph families and matching on symmetric ones.
DPD-Lasso integrates density power divergence and Lasso regularization into an iterative algorithm for stable regression on clean and contaminated data from MII aerosol jet printing experiments.
citing papers explorer
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UMVUE-Type Estimators under Bregman Losses
Extends UMVUE theory to Bregman losses by introducing dual-space unbiasedness and proving Rao-Blackwell and Lehmann-Scheffé analogs for type-I Bregman UMVUEs.
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ADI schemes for heat equations with irregular boundaries and interfaces in 3D with applications
KFBI-ADI schemes achieve second-order accuracy and unconditional stability for 3D heat equations with irregular boundaries and interfaces, verified numerically and applied to Stefan problems with level sets.
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Graph Isomorphism: Mixed-Integer Convex Optimization from First-Order Methods
A mixed-integer convex formulation for graph isomorphism is solved via first-order methods and variable fixing, outperforming integer feasibility on 6 of 12 graph families and matching on symmetric ones.
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Robust Analysis for Resilient AI System
DPD-Lasso integrates density power divergence and Lasso regularization into an iterative algorithm for stable regression on clean and contaminated data from MII aerosol jet printing experiments.