298 citations · 1.2k across the 24 of their papers we have counts for
5 papers · 1 filter
A note on the approximate admissibility of regularized estimators in the Gaussian sequence model
Xi Chen, Adityanand Guntuboyina, Yuchen Zhang
We study the problem of estimating an unknown vector from an observation drawn according to the normal distribution with mean and identity covariance matrix under the k…
Optimal prediction for sparse linear models? Lower bounds for coordinate-separable M-estimators
Yuchen Zhang, Martin J. Wainwright, Michael I. Jordan
For the problem of high-dimensional sparse linear regression, it is known that an -based estimator can achieve a "fast" rate on the prediction error without any condi…
On Bayes Risk Lower Bounds
Xi Chen, Adityanand Guntuboyina, Yuchen Zhang
This paper provides a general technique for lower bounding the Bayes risk of statistical estimation, applicable to arbitrary loss functions and arbitrary prior distributions. A low…
Lower bounds on the performance of polynomial-time algorithms for sparse linear regression
Yuchen Zhang, Martin J. Wainwright, Michael I. Jordan
Under a standard assumption in complexity theory (NP not in P/poly), we demonstrate a gap between the minimax prediction risk for sparse linear regression that can be achieved by p…
Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates
Yuchen Zhang, John C. Duchi, Martin J. Wainwright
We establish optimal convergence rates for a decomposition-based scalable approach to kernel ridge regression. The method is simple to describe: it randomly partitions a dataset of…