research
∙
03/31/2023
Simple Sorting Criteria Help Find the Causal Order in Additive Noise Models
Additive Noise Models (ANM) encode a popular functional assumption that ...
share
research
∙
01/25/2023
Inference in Marginal Structural Models by Automatic Targeted Bayesian and Minimum Loss-Based Estimation
Two of the principle tasks of causal inference are to define and estimat...
research
∙
06/23/2022
Anticipating the cost of drought events in France by super learning
Drought events are the second most expensive type of natural disaster wi...
research
∙
09/21/2021
Personalized Online Machine Learning
In this work, we introduce the Personalized Online Super Learner (POSL) ...
research
∙
07/28/2021
One-step ahead sequential Super Learning from short times series of many slightly dependent data, and anticipating the cost of natural disasters
Suppose that we observe a short time series where each time-t-specific d...
research
∙
07/15/2021
Optimal tests of the composite null hypothesis arising in mediation analysis
The indirect effect of an exposure on an outcome through an intermediate...
research
∙
06/03/2021
Risk Minimization from Adaptively Collected Data: Guarantees for Supervised and Policy Learning
Empirical risk minimization (ERM) is the workhorse of machine learning, ...
research
∙
06/01/2021
Post-Contextual-Bandit Inference
Contextual bandit algorithms are increasingly replacing non-adaptive A/B...
research
∙
06/05/2020
Rate-adaptive model selection over a collection of black-box contextual bandit algorithms
We consider the model selection task in the stochastic contextual bandit...
research
∙
03/05/2020
Generalized Policy Elimination: an efficient algorithm for Nonparametric Contextual Bandits
We propose the Generalized Policy Elimination (GPE) algorithm, an oracle...
research
∙
03/31/2018
Collaborative targeted inference from continuously indexed nuisance parameter estimators
We wish to infer the value of a parameter at a law from which we sample ...
research
∙
03/31/2018
Collaborative targeted minimum loss inference from continuously indexed nuisance parameter estimators
Suppose that we wish to infer the value of a statistical parameter at a ...
research
∙
06/30/2016
