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The Power of Preconditioning in Overparameterized Low-Rank Matrix Sensing
We propose $\textsf{ScaledGD($\lambda$)}$, a preconditioned gradient descent method to tackle the low-rank matrix sensing problem when the true rank is unknown, and when the matrix is possibly ill-conditioned.
Nonparametric mixture MLEs under Gaussian-smoothed optimal transport distance
The Gaussian-smoothed optimal transport (GOT) framework, pioneered in Goldfeld et al. (2020) and followed up by a series of subsequent papers, has quickly caught attention among researchers in statistics, machine learning, information theory, and related fields.
Uncertainty quantification in the Bradley-Terry-Luce model
The Bradley-Terry-Luce (BTL) model is a benchmark model for pairwise comparisons between individuals.
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