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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3 results for “post-stratification”

Variance Reduction for Heavy-Tailed Monetization Metrics in Ranking Experiments via Post-Stratificationcs.LG

We reduce variance in monetization metrics for ranking experiments.

problem Heavy-tailed monetization metrics lead to unreliable conclusions in A/B experiments.

method Post-stratification combined with CUPED.

result Significant reduction in variance and improved decision stability.

variance reduction monetization metrics ranking experiments post-stratification CUPED

2026-06-02abs ↗pdf ↗

Learning from Biased and Costly Data Sources: Minimax-optimal Data Collection under a Budgetstat.ML

Study optimizes data collection from biased, costly sources to minimize risk.

problem Estimating population means and group-conditional means from multiple sources with varying costs and biases.

method Develops a sampling plan that maximizes effective sample size, paired with a post-stratification estimator.

result Achieves budgeted minimax optimal risk for estimating population means and group-conditional means.

data collection multi-source learning heterogeneous data costly sources minimax optimization

2026-02-19abs ↗pdf ↗

Using Auxiliary Data to Boost Precision in the Analysis of A/B Tests on an Online Educational Platform: New Data and New Resultsstat.ME

Boosts A/B test precision using auxiliary data from historical users.

problem Small sample sizes and imprecise estimates in A/B tests.

method Coupling design-based causal estimation with machine-learning models of historical user data.

result Effect estimates using auxiliary data are roughly equivalent to increasing sample size by 20%, or up to 50-80% in some cases.

A/B tests auxiliary data precision boost online education causal estimation

2023-06-09abs ↗pdf ↗