collaborators

19 papers

stat.ME2026

Design-Based Anytime-Valid Inference for Randomized Experiments with Delayed Outcomes and Staggered Entry

Michael Lindon, Nathan Kallus

Delayed outcomes are ubiquitous in online experimentation: treatment can affect whether an outcome occurs, when it occurs, and its realized value. To accommodate staggered entry wh…

cs.LG2026

Entropy After </Think> for reasoning model early exiting

Xi Wang, James McInerney, Lequn Wang +1

Reasoning LLMs show improved performance with longer chains of thought. However, recent work has highlighted their tendency to overthink, continuing to revise answers even after re…

stat.ME2026

GAAVI: Global Asymptotic Anytime Valid Inference for the Conditional Mean Function

Brian M Cho, Raaz Dwivedi, Nathan Kallus

Inference on the conditional mean function (CMF) is central to tasks from adaptive experimentation to optimal treatment assignment and algorithmic fairness auditing. In this work,…

cs.LG2026

Causal Inference on Networks under Misspecified Exposure Mappings: A Partial Identification Framework

Maresa Schröder, Miruna Oprescu, Stefan Feuerriegel +1

Estimating treatment effects in networks is challenging, as each potential outcome depends on the treatments of all other nodes in the network. To overcome this difficulty, existin…

cs.LG2025

Exploration in the Limit

Brian M. Cho, Nathan Kallus

In fixed-confidence best arm identification (BAI), the objective is to quickly identify the optimal option while controlling the probability of error below a desired threshold. Des…

math.ST2025

Experimentation Under Non-stationary Interference

Su Jia, Peter Frazier, Nathan Kallus +1

We study the estimation of the ATE in randomized controlled trials under a dynamically evolving interference structure. This setting arises in applications such as ride-sharing, wh…