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A finite sample analysis of the benign overfitting phenomenon for ridge function estimation
Recent extensive numerical experiments in high scale machine learning have allowed to uncover a quite counterintuitive phase transition, as a function of the ratio between the sample size and the number of parameters in the model.
Average performance analysis of the stochastic gradient method for online PCA
This paper studies the complexity of the stochastic gradient algorithm for PCA when the data are observed in a streaming setting.
Feature selection in weakly coherent matrices
A problem of paramount importance in both pure (Restricted Invertibility problem) and applied mathematics (Feature extraction) is the one of selecting a submatrix of a given matrix, such that this submatrix has its smallest singular value above a specified level.
Convex recovery of tensors using nuclear norm penalization
The subdifferential of convex functions of the singular spectrum of real matrices has been widely studied in matrix analysis, optimization and automatic control theory.
