42 citations · 95 across the 11 of their papers we have counts for
4 papers · 1 filter
On the Computational Efficiency of Bayesian Additive Regression Trees: An Asymptotic Analysis
Yan Shuo Tan, Omer Ronen, Theo Saarinen +1
Bayesian Additive Regression Trees (BART) is a popular Bayesian non-parametric regression model that is commonly used in causal inference and beyond. Its strong predictive performa…
A Mixing Time Lower Bound for a Simplified Version of BART
Omer Ronen, Theo Saarinen, Yan Shuo Tan +2
Bayesian Additive Regression Trees (BART) is a popular Bayesian non-parametric regression algorithm. The posterior is a distribution over sums of decision trees, and predictions ar…
A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds
Yan Shuo Tan, Abhineet Agarwal, Bin Yu
Decision trees are important both as interpretable models amenable to high-stakes decision-making, and as building blocks of ensemble methods such as random forests and gradient bo…
Online Stochastic Gradient Descent with Arbitrary Initialization Solves Non-smooth, Non-convex Phase Retrieval
Yan Shuo Tan, Roman Vershynin
In recent literature, a general two step procedure has been formulated for solving the problem of phase retrieval. First, a spectral technique is used to obtain a constant-error in…