15 citations · 15 across the 2 of their papers we have counts for
2 papers
stat.ML2020★ 15 cited
The estimation error of general first order methods
Michael Celentano, Andrea Montanari, Yuchen Wu
Modern large-scale statistical models require to estimate thousands to millions of parameters. This is often accomplished by iterative algorithms such as gradient descent, projecte…
math.ST2019
Approximate separability of symmetrically penalized least squares in high dimensions: characterization and consequences
Michael Celentano
We show that the high-dimensional behavior of symmetrically penalized least squares with a possibly non-separable, symmetric, convex penalty in both (i) the Gaussian sequence model…