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Multitask diffusion LMS with sparsity-based regularization

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Multitask diffusion LMS with sparsity-based regularization

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Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Saddle-to-Saddle Dynamics in Diagonal Linear Networks

System and method for transcoding spectral data with task-based optimization via symmetric non-negative matrix factorization

Last iterate convergence of SGD for Least-Squares in the Interpolation regime

Sparsely Observed Functional Time Series: Theory and Applications

Model-Class Selection Using Clustering and Classification for Structural Identification and Prediction

Some first results on the consistency of spatial regression with partial differential equation regularization

Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization

Spatially Varying Monte Carlo SURE for the Regularization of Biomedical Images

Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces