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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9 results for “R-learner”

Multi-Study R-Learner for Estimating Heterogeneous Treatment Effects Across Studies Using Statistical Machine Learningstat.ME

A new method estimates treatment effects across multiple studies considering differences.

problem Estimating treatment effects across multiple studies with varying conditions.

method The multi-study R-learner framework that accounts for between-study heterogeneity.

result The multi-study R-learner is more efficient and normal than existing methods in the presence of heterogeneity.

treatment effects heterogeneity multi-study statistical machine learning R-learner

2023-06-01abs ↗pdf ↗

Statistical Learning for Heterogeneous Treatment Effects: Pretraining, Prognosis, and Predictionstat.ML

The paper proposes a method to estimate heterogeneous treatment effects using pretraining strategies.

problem Estimating conditional average treatment effects (CATE) in the presence of many covariates.

method The approach leverages prognostic factors that also predict treatment effect heterogeneity, using the R-learner framework.

result The proposed method improves estimation accuracy and power for detecting treatment effect heterogeneity.

heterogeneous treatment effects prognostic factors R-learner framework machine learning causal estimation

2025-05-01abs ↗pdf ↗

Structured Difference-of-Q via Orthogonal Learningstat.ML

New method estimates and optimizes policy differences using orthogonal learning.

problem Offline reinforcement learning with safety concerns and cost limitations.

method Dynamic R-learner for estimating and optimizing

Q^π(s,1)-Q^π(s,0)

, leveraging orthogonal estimation.

result Consistent policy optimization with improved convergence rates.

reinforcement learning offline learning policy optimization orthogonal learning causal inference

2024-06-12abs ↗pdf ↗

Debiased Front-Door Learners for Heterogeneous Effectsstat.ML

Debiased learners estimate heterogeneous treatment effects in observational studies.

problem Estimating heterogeneous treatment effects in observational studies with unmeasured confounders.

method Debiased Front-Door (FD) learners, FD-DR-Learner and FD-R-Learner, under specific assumptions.

result Debiased learners satisfy error bounds and stage-error decompositions, delivering reliable HTE estimates.

observational studies heterogeneous treatment effects front-door adjustment mediators unmeasured confounders

2025-09-26abs ↗pdf ↗

Differentially Private Estimation of Heterogeneous Causal Effectsstat.ML

The paper introduces a privacy-preserving method for estimating treatment effects that maintains accuracy.

problem Estimating heterogeneous treatment effects in sensitive data while protecting privacy.

method A general meta-algorithm for CATE estimation with differential privacy guarantees, using sample splitting and parallel composition.

result The meta-algorithm maintains accuracy even with differential privacy, showing that most accuracy loss is due to variance increase.

differential privacy causal inference heterogeneous treatment effects privacy-preserving estimation sample splitting

2022-02-22abs ↗pdf ↗

Combining T-learning and DR-learning: a framework for oracle-efficient estimation of causal contrastsstat.ML

EP-learning framework improves causal contrast estimation efficiency.

problem Estimating heterogeneous causal contrasts efficiently and stably.

method EP-learning framework combining T-learning and DR-learning.

result EP-learners are oracle-efficient and outperform competitors.

EP-learning causal contrasts T-learning DR-learning oracle efficiency

2024-02-03abs ↗pdf ↗

Orthogonal Survival Learners for Estimating Heterogeneous Treatment Effects from Time-to-Event Datacs.LG

New survival learners estimate heterogeneous treatment effects from time-to-event data.

problem Estimating HTEs from time-to-event data with censoring outcomes.

method Orthogonal survival learners with theoretical guarantees and custom weighting functions.

result Orthogonal survival learners provide robust and model-agnostic HTE estimation.

Heterogeneous Treatment Effects Survival Analysis Time-to-Event Data Orthogonal Learners Censoring

2025-05-19abs ↗pdf ↗

Heterogeneous Causal Learning for Effectiveness Optimization in User Marketingcs.LG

Optimizes user marketing campaigns to balance cost and effectiveness.

problem Lack of methods to optimize marketing campaigns considering cost and effectiveness.

method Proposes a treatment effect optimization algorithm using deep learning to balance cost and effectiveness.

result Demonstrates superior performance in cost-efficiency and real-world business value.

user marketing treatment effect optimization deep learning cost efficiency business metrics

2020-04-21abs ↗pdf ↗

Orthogonal machine learning for conditional odds and risk ratiosstat.ML

New methods for estimating conditional odds and risk ratios improve treatment decision rules.

problem Estimation of conditional odds and risk ratios lags behind conditional average treatment effects.

method Proposed novel estimators based on doubly robust transformations and orthogonal risk functions.

result Proposed estimators significantly reduce bias and mean squared error in complex settings.

conditional odds risk ratios doubly robust orthogonal risk functions Monte Carlo simulation

2026-04-12abs ↗pdf ↗