On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,742 papers · 148 categories

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5 results for “rerandomization”

Fast Rerandomization for Balancing Covariates in Randomized Experiments: A Metropolis-Hastings Frameworkstat.ME

A new algorithm speeds up rerandomization for better experiment balance.

problem Achieving optimal covariate balance in randomized experiments.

method Metropolis-Hastings framework with sampling-importance resampling.

result PSRSRR achieves significant speedups while maintaining statistical guarantees.

rerandomization covariate balance Metropolis-Hastings sampling-importance resampling speedup

2026-02-07abs ↗pdf ↗

DARTS: Targeting Prognostic Covariates in Budget-Constrained Sequential Experimentsstat.ML

DARTS optimizes covariate selection in trials with limited data.

problem Limited budget for high-dimensional pretreatment data.

method Dynamic Adaptive Rerandomization via Thompson Sampling (DARTS).

result DARTS efficiently concentrates budget on informative features.

covariate selection sequential optimization Thompson sampling causal inference budget-constrained

2026-05-07abs ↗pdf ↗

WHOMP: Optimizing Randomized Controlled Trials via Wasserstein Homogeneitystat.ML

WHOMP optimizes randomized controlled trials by minimizing subgroup bias.

problem Minimizing subgroup bias in randomized controlled trials.

method Wasserstein Homogeneity Partition (WHOMP) method.

result WHOMP optimally minimizes type I and type II errors in trials.

Randomized Controlled Trials Wasserstein Distance Subgroup Bias Optimization Type I and Type II Errors

2024-09-27abs ↗pdf ↗

In Defense of Uniform Convergence: Generalization via derandomization with an application to interpolating predictorscs.LG

New method reduces generalization error for interpolating predictors.

problem Understanding and reducing generalization error for predictors that interpolate training data.

method Derandomization and conditional distribution to control generalization error.

result Surrogates constructed by conditioning and denoising have uniformly small generalization error.

generalization error interpolating predictors derandomization conditional distribution predictor risk

2019-12-09abs ↗pdf ↗

On the Optimality of Randomization in Experimental Design: How to Randomize for Minimax Variance and Design-Based Inferencestat.ME

Randomization is minimax-optimal for variance in experimental design, even with structure.

problem Designing optimal randomized experiments for variance minimization.

method Analyzing permutation symmetric and non-symmetric sets of outcomes, proposing inference-constrained MSOD.

result Randomization is minimax-optimal for variance, even with structure, and requires uniformity constraints for Fisher's exact test.

randomization experimental design minimax variance minimization uniformity constraints

2020-05-06abs ↗pdf ↗