Applied Mathematics
Printer-friendly versionDual Principal Component Pursuit
A Fast, Stable QR Algorithm for the Diagonalization of Colleague Matrices
New Methods for Low-Rank Matrix Denoising
The Polyak-Lojasiewicz condition as a framework for over-parameterized optimization and its application to deep learning
Fast & Accurate Randomized Algorithms for Linear Systems and Eigenvalue Problems
Kernel two-sample test: on manifold data and by neural tangent kernel
Manifold learning with non-Euclidean norms, and orbit recovery
How to apply manifold learning and random matrix theory to study complicated time series?
Uncertainties and inference in physical dynamics
