Modulation Spaces and the Curse of Dimensionality

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Modulation Spaces and the Curse of Dimensionality

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Spectral Estimators for High-Dimensional Matrix Inference

Analysis of Bootstrap and Subsampling in High-dimensional Regularized Regression

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Scalable and Privacy-Preserving Federated Principal Component Analysis

Fluctuations, bias, variance and ensemble of learners: exact asymptotics for convex losses in high-dimension

Structure-preserving approaches and data-driven closure modeling for model order reduction

Filtered data and eigenfunction estimators for statistical inference of multiscale and interacting diffusion processes

Statistical Applications of Random Matrix Theory: Comparison of Two Populations

Streaming Principal Component Analysis From Incomplete Data

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Graph-based Methods for Visualization and Clustering

Fast Robust PCA on Graphs

LDAHash: Improved Matching with Smaller Descriptors

Efficient Schemes for Adaptive Frequency Tracking and their Relevance for EEG and ECG