69 citations · 261 across the 20 of their papers we have counts for
5 papers · 1 filter
Bayesian Bootstrap Spike-and-Slab LASSO
Lizhen Nie, Veronika Ročková
The impracticality of posterior sampling has prevented the widespread adoption of spike-and-slab priors in high-dimensional applications. To alleviate the computational burden, opt…
Spike-and-Slab Meets LASSO: A Review of the Spike-and-Slab LASSO
Ray Bai, Veronika Rockova, Edward I. George
High-dimensional data sets have become ubiquitous in the past few decades, often with many more covariates than observations. In the frequentist setting, penalized likelihood metho…
The art of BART: Minimax optimality over nonhomogeneous smoothness in high dimension
Seonghyun Jeong, Veronika Rockova
Many asymptotically minimax procedures for function estimation often rely on somewhat arbitrary and restrictive assumptions such as isotropy or spatial homogeneity. This work enhan…
Variable Selection via Thompson Sampling
Yi Liu, Veronika Rockova
Thompson sampling is a heuristic algorithm for the multi-armed bandit problem which has a long tradition in machine learning. The algorithm has a Bayesian spirit in the sense that…
Uncertainty Quantification for Sparse Deep Learning
Yuexi Wang, Veronika Ročková
Deep learning methods continue to have a decided impact on machine learning, both in theory and in practice. Statistical theoretical developments have been mostly concerned with ap…