← Search

Aleksandr Aravkin

2 accepted papers

2019

Robust Singular Smoothers for Tracking Using Low-Fidelity Data

RSS 2019poster

Tracking underwater autonomous platforms is often challenged by noisy, biased, and discretized input data. Classic filters and smoothers based on standard assumptions of Gaussian white noise break down when presented with any of these challenges. Robust models (such as the Huber loss) and constraint…

Cited by 0SourcePDFScholar
2019

Trimming the $\ell_1$ Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning

ICML 2019oral

We study high-dimensional estimators with the trimmed $\ell_1$ penalty, which leaves the h largest parameter entries penalty-free. While optimization techniques for this nonconvex penalty have been studied, the statistical properties have not yet been analyzed. We present the first statistical analy…