58 citations · 276 across the 26 of their papers we have counts for
7 papers · 1 filter
Exact Asymptotics for Linear Quadratic Adaptive Control
Feicheng Wang, Lucas Janson
Recent progress in reinforcement learning has led to remarkable performance in a range of applications, but its deployment in high-stakes settings remains quite rare. One reason is…
Powerful Knockoffs via Minimizing Reconstructability
Asher Spector, Lucas Janson
Model-X knockoffs allows analysts to perform feature selection using almost any machine learning algorithm while still provably controlling the expected proportion of false discove…
A Power Analysis of the Conditional Randomization Test and Knockoffs
Wenshuo Wang, Lucas Janson
In many scientific problems, researchers try to relate a response variable to a set of potential explanatory variables , and start by trying to identify va…
Cross-validation Confidence Intervals for Test Error
Pierre Bayle, Alexandre Bayle, Lucas Janson +1
This work develops central limit theorems for cross-validation and consistent estimators of its asymptotic variance under weak stability conditions on the learning algorithm. Toget…
Floodgate: inference for model-free variable importance
Lu Zhang, Lucas Janson
Many modern applications seek to understand the relationship between an outcome variable and a covariate in the presence of a (possibly high-dimensional) confounding variab…
Fast and Powerful Conditional Randomization Testing via Distillation
Molei Liu, Eugene Katsevich, Lucas Janson +1
We consider the problem of conditional independence testing: given a response Y and covariates (X,Z), we test the null hypothesis that Y is independent of X given Z. The conditiona…