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.

168,695 papers · 148 categories

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13 results for “undersmoothing”

Double Cross-fit Doubly Robust Estimators: Beyond Series Regressionmath.ST

Improved estimators for causal inference using cross-fitting and undersmoothing.

problem Estimating expected conditional covariance in causal inference.

method Double cross-fit doubly robust (DCDR) estimators with undersmoothing for non-smooth nuisance functions.

result DCDR estimators achieve

\sqrt{n}

-consistency and asymptotic normality under minimal conditions.

causal inference doubly robust cross-fitting undersmoothing expected conditional covariance

2024-03-22abs ↗pdf ↗

Augmented balancing weights as linear regressionstat.ME

Novel characterization of augmented balancing weights combining outcome and weighting models.

problem Improving estimation accuracy in machine learning models with balancing weights.

method Characterization of augmented balancing weights as linear models, extending to ridge and lasso regression.

result Equivalence and closed-form expressions for specific model choices, providing insights into performance.

augmented balancing weights doubly robust estimators de-biased machine learning kernel ridge regression lasso penalized regression

2023-04-27abs ↗pdf ↗

Constructing optimal treatment length strategies to maximize quality-adjusted lifetimesmath.ST

Optimizes treatment duration to maximize quality-adjusted lifetime.

problem Balancing risks and benefits in clinical decision making.

method Proposes a weighted estimating equation to adjust for confounding and informative censoring, and a nonparametric estimator for mean counterfactual quality-adjusted lifetime.

result Shows the optimal time for percutaneous endoscopic gastrostomy insertion in ALS patients.

clinical decision making quality-adjusted lifetime treatment length informative censoring weighted estimating equation

2024-12-06abs ↗pdf ↗

Nonparametric estimation of a covariate-adjusted counterfactual treatment regimen response curvemath.ST

Estimates personalized treatment response curves using covariates.

problem Flexible estimation of personalized treatment response curves.

method Sieve based nonparametric estimator of smoothed regimen-response curve function.

result Asymptotic linearity and undersmoothing criteria for efficient estimation.

personalized medicine covariate adjustment counterfactual treatment value function nonparametric estimation

2023-09-28abs ↗pdf ↗

Difference-in-Differences with Time-varying Continuous Treatments using Double/Debiased Machine Learningecon.EM

Estimates the effect of time-varying treatments using machine learning.

problem Estimating the impact of time-varying treatments over multiple periods.

method Difference-in-Differences framework with double/debiased machine learning.

result Higher vaccination rates reduce COVID-19 mortality after several weeks.

Difference-in-Differences Time-varying treatments Machine learning COVID-19 Vaccination

2024-10-28abs ↗pdf ↗

Adaptive Estimation and Uniform Confidence Bands for Nonparametric Structural Functions and Elasticitiesecon.EM

New methods for estimating and inferring nonparametric structural functions and elasticities.

problem Estimating and inferring nonparametric structural functions and their derivatives.

method Data-driven sieve dimension choice and uniform confidence bands construction.

result Optimal estimation and inference procedures with minimax rates of convergence.

nonparametric estimation structural functions elasticities instrumental variables uniform confidence bands

2021-07-25abs ↗pdf ↗

Direct Estimation of Schrödinger Bridge Time-Series Drifts: Finite-Sample, Asymptotic, and Adaptive Guaranteesmath.ST

Estimates time-series drifts from i.i.d. data using a direct Nadaraya-Watson plug-in method.

problem Nonparametric estimation of Schrödinger bridge drifts from single time interval data.

method Direct Nadaraya-Watson plug-in estimator based on kernelized numerator and denominator terms.

result Uniform non-asymptotic bound, CLT under undersmoothing, and adaptive bandwidth selector.

Schrödinger bridge time-series drift Nadaraya-Watson kernelized estimation finite-sample analysis

2026-05-06abs ↗pdf ↗

Asymptotic Bounds for Smoothness Parameter Estimates in Gaussian Process Interpolationmath.ST

The paper establishes bounds on the smoothness parameter in Gaussian process interpolation.

problem Estimating the smoothness parameter in Gaussian process models.

method Approximation theory in Sobolev spaces and general theorems on parameter estimation.

result Maximum likelihood estimation recovers the true smoothness for certain classes of functions.

Gaussian process Matérn kernel smoothness parameter approximation theory Sobolev spaces

2022-03-10abs ↗pdf ↗

Nuisance Function Tuning and Sample Splitting for Optimally Estimating a Doubly Robust Functionalmath.ST

Optimally estimates a functional using nuisance function tuning and sample splitting.

problem Estimating optimal rates for a doubly robust functional.

method Combines nuisance function tuning and sample splitting strategies.

result Shows optimal rates of convergence for various estimators.

doubly robust functional estimation nuisance function sample splitting optimal rates

2022-12-30abs ↗pdf ↗

Nonparametric inverse probability weighted estimators based on the highly adaptive lassostat.ME

New nonparametric estimators improve causal effect estimation.

problem Estimation of causal effects with selection bias.

method Undersmoothing of the highly adaptive lasso for estimating the weighting mechanism.

result Asymptotic efficiency and convergence to nonparametric efficiency bound.

inverse probability weighting highly adaptive lasso causal inference nonparametric estimation asymptotic efficiency

2020-05-22abs ↗pdf ↗

Causal Effect Estimation with TMLE: Handling Missing Data and Near-Violations of Positivitystat.ME

TMLE improves causal effect estimation in missing data scenarios with various positivity violations.

problem Estimating causal effects in studies with missing data and positivity violations.

method Targeted Maximum Likelihood Estimation (TMLE) with various missing data methods.

result Complete cases with TMLE incorporating an outcome-missingness model exhibit lower bias and greater robustness against positivity violations.

TMLE missing data positivity violations causal inference bias reduction

2025-10-25abs ↗pdf ↗

A Generalized Adaptive Joint Learning Framework for High-Dimensional Time-Varying Modelsstat.ME

AJL framework detects dynamic patterns in high-dimensional time-varying models.

problem Complex time-varying associations and abrupt regime shifts in longitudinal processes.

method Hierarchical regularization framework integrating functional variable selection with structural changepoint detection.

result The refined estimator achieves the oracle property in ultra-high-dimensional settings.

Adaptive Joint Learning Functional Data Analysis Changepoint Detection Multivariate Time-Varying Models Sure Screening Consistency

2026-01-08abs ↗pdf ↗

Estimation of population size based on capture recapture designs and evaluation of the estimation reliabilitymath.ST

Estimates population size using capture-recapture designs with binary indicators.

problem Estimating population size from capture-recapture data with binary indicators.

method Proposes a modern method using undersmoothed lasso model to estimate the target parameter of interest.

result The choice of constraint on the K-dimensional distribution significantly impacts the value of the estimand.

capture-recapture population size estimation binary indicators lasso model log-linear model

2021-05-12abs ↗pdf ↗