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stat.CO2026
Scalable Statistical Inference in Stochastic Gradient Descent
Rahul Singh, Abhinek Shukla
Constructing confidence regions for stochastic gradient descent (SGD) ideally requires estimating the asymptotic covariance matrix, a severe computational bottleneck in high dimens…
stat.ME2026
Generated outcomes as generated regressors: Equivalences in recursive causal estimation
Wisse Rutgers, Rahul Singh
Time-varying treatment effects, surrogate-identified treatment effects, and mediation effects can all be written as recursive regressions, in which each regression's predicted valu…
stat.ME2026
Testing for lack of fit in paired comparison data
Rahul Singh, Ori Davidov
Linear stochastic transitivity is a central assumption in paired comparison models that is rarely verified in practice. Empirical violations, however, are common and can substantia…