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Eigendecomposition-Free Training of Deep Networks for Linear Least-Square Problems

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Eigendecomposition-Free Training of Deep Networks for Linear Least-Square Problems

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Neural Tanget Kernel: Convergence and Generalization in Neural Networks

Learning to Find Good Correspondences

Learning to Find Good Correspondences

Robustness of Classifiers to Universal Perturbations: A Geometric Perspective

Smoothing Alternating Direction Methods for Fully Nonsmooth Constrained Convex Optimization

Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression

Reconstruction of 3D scattered data via radial basis functions by efficient and robust techniques

Case Study of Data Assimilation Methods with the LWR-Proteus Phase II Experimental Campaign

ALS Scheme using Extent-based Constraints for the Analysis of Chemical Reaction Systems

Low-rank methods for parameter-dependent eigenvalue problems and matrix equations

Learning to Find Good Correspondences

Learning to Find Good Correspondences

Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression

Neural Tanget Kernel: Convergence and Generalization in Neural Networks

Robustness of Classifiers to Universal Perturbations: A Geometric Perspective

Reconstruction of 3D scattered data via radial basis functions by efficient and robust techniques

Smoothing Alternating Direction Methods for Fully Nonsmooth Constrained Convex Optimization

Case Study of Data Assimilation Methods with the LWR-Proteus Phase II Experimental Campaign

ALS Scheme using Extent-based Constraints for the Analysis of Chemical Reaction Systems

Low-rank methods for parameter-dependent eigenvalue problems and matrix equations