Introduces a unified abstract framework for randomized subspace correction methods with convergence analysis for convex optimization under general assumptions.
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A novel high-order stabilization-free virtual element method is developed for general second-order elliptic eigenvalue problems, with optimal a priori error estimates for eigenspaces and eigenvalues, validated on various polygonal meshes.
Develops an evolving finite element method for parabolic PDEs with evolving interfaces, derives a suitable weak formulation, proves optimal error bounds for isoparametric elements of arbitrary order, and verifies convergence numerically.
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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Randomized subspace correction methods for convex optimization
Introduces a unified abstract framework for randomized subspace correction methods with convergence analysis for convex optimization under general assumptions.
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A high order stabilization-free virtual element method for general second-order elliptic eigenvalue problem
A novel high-order stabilization-free virtual element method is developed for general second-order elliptic eigenvalue problems, with optimal a priori error estimates for eigenspaces and eigenvalues, validated on various polygonal meshes.
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Evolving finite elements for advection diffusion with an evolving interface
Develops an evolving finite element method for parabolic PDEs with evolving interfaces, derives a suitable weak formulation, proves optimal error bounds for isoparametric elements of arbitrary order, and verifies convergence numerically.
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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.