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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.

168,694 papers · 148 categories

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5 results for “outcome-adapted”

Outcome-adapted Automatic Debiased Machine Learningstat.ME

Improved AutoDML estimator for causal inference using outcome-adapted shared covariate representation.

problem Efficiency in estimating treatment or policy effects in causal inference.

method Outcome-adapted AutoDML estimator that uses a shared covariate representation that is predictive of the outcome but not the Riesz representer.

result Outcome-adapted AutoDML estimator is asymptotically more efficient than baseline AutoDML.

causal inference outcome-adapted AutoDML shared representation Riesz representer

2026-07-03abs ↗pdf ↗

Robust inference on the average treatment effect using the outcome highly adaptive lassostat.ME

Many estimators of the average effect of a treatment on an outcome require estimation of the propensity score, the outcome regression, or both. It is often beneficial to utilize flexible techniques such as semiparametric regression or machine learning to estimate these quantities. However, optimal estimation of these r…

2018-06-18abs ↗pdf ↗

Measuring Neural Network Complexity via Effective Degrees of Freedomstat.ME

Measures neural network complexity via effective degrees of freedom.

problem Challenges in quantifying neural network complexity.

method Adapts generalized degrees of freedom (GDF) for binary outcomes and compares with cross-validation and null degrees of freedom.

result GDF provides a robust measure of model complexity for neural networks.

neural networks model complexity degrees of freedom log-likelihood binary outcomes

2026-02-13abs ↗pdf ↗

Efficient adjustment for complex covariates: Gaining efficiency with DOPEmath.ST

DOPE efficiently estimates ATE with complex covariates.

problem Efficient estimation of ATE from complex covariates.

method Proposed DOPE framework for efficient adjustment.

result DOPE retains efficiency even with highly predictive covariates.

covariate adjustment ATE estimation DOPE propensity weighting neural networks

2024-02-20abs ↗pdf ↗

Model-free Methods for Event History Analysis and Efficient Adjustment (PhD Thesis)stat.ME

Develops model-free methods for event history analysis and efficient covariate adjustment.

problem Estimating treatment effects while accounting for confounding and understanding event history.

method Model-free prediction techniques, Local Covariance Measure (LCM), Debiased Outcome-adapted Propensity Estimator (DOPE), Aalen Covariance Measure (ACM).

result Demonstrates the effectiveness and robustness of the proposed methods in various settings.

event history analysis covariate adjustment model-free methods machine learning local independence

2025-02-11abs ↗pdf ↗