Cover Image

STEEL: Singularity-aware Reinforcement Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chen, Xiaohong, Qi, Zhengling, Wan, Runzhe
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Econometrics Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Adaptive, Rate-Optimal Hypothesis Testing in Nonparametric IV Models
by: Breunig, Christoph, et al.
Published: (2020)

Adaptive Estimation and Uniform Confidence Bands for Nonparametric Structural Functions and Elasticities
by: Chen, Xiaohong, et al.
Published: (2021)

Quantile-Optimal Policy Learning under Unmeasured Confounding
by: Chen, Zhongren, et al.
Published: (2025)

Machine-Learning-Assisted Comparison of Regression Functions
by: Yan, Jian, et al.
Published: (2025)

Deep Learning With DAGs
by: Balgi, Sourabh, et al.
Published: (2024)

An Introduction to Double/Debiased Machine Learning
by: Ahrens, Achim, et al.
Published: (2025)

Data-Automated Policy Learning for Nonlinear Welfare
by: Ai, Chunrong, et al.
Published: (2026)

Robust and Agnostic Learning of Conditional Distributional Treatment Effects
by: Kallus, Nathan, et al.
Published: (2022)

Individualized Policy Evaluation and Learning under Clustered Network Interference
by: Zhang, Yi, et al.
Published: (2023)

Estimating Causal Effects with Double Machine Learning -- A Method Evaluation
by: Fuhr, Jonathan, et al.
Published: (2024)

Covariate-Adjusted Deep Causal Learning for Heterogeneous Panel Data Models
by: Zhou, Guanhao, et al.
Published: (2025)

Double Machine Learning meets Panel Data -- Promises, Pitfalls, and Potential Solutions
by: Fuhr, Jonathan, et al.
Published: (2024)

Transfer Learning for Spatial Autoregressive Models with Application to U.S. Presidential Election Prediction
by: Zeng, Hao, et al.
Published: (2024)

Double Machine Learning for Static Panel Data with Instrumental Variables: New Method and Applications
by: Baiardi, Anna, et al.
Published: (2026)

xtdml: Double Machine Learning Estimation to Static Panel Data Models with Fixed Effects in R
by: Polselli, Annalivia
Published: (2025)

Machine Learning Who to Nudge: Causal vs Predictive Targeting in a Field Experiment on Student Financial Aid Renewal
by: Athey, Susan, et al.
Published: (2023)

Partial Identification under Missing Data Using Weak Shadow Variables from Pretrained Models
by: Chen, Hongyu, et al.
Published: (2026)

Tackling Interference Induced by Data Training Loops in A/B Tests: A Weighted Training Approach
by: Si, Nian
Published: (2023)

Synthetic Combinations: A Causal Inference Framework for Combinatorial Interventions
by: Agarwal, Abhineet, et al.
Published: (2023)

Adaptive Student's t-distribution with method of moments moving estimator for nonstationary time series
by: Duda, Jarek
Published: (2023)

Double Debiased Covariate Shift Adaptation Robust to Density-Ratio Estimation
by: Kato, Masahiro, et al.
Published: (2023)

Adaptive Principal Component Regression with Applications to Panel Data
by: Agarwal, Anish, et al.
Published: (2023)

The Bayesian Context Trees State Space Model for time series modelling and forecasting
by: Papageorgiou, Ioannis, et al.
Published: (2023)

Estimating the Value of Evidence-Based Decision Making
by: Abadie, Alberto, et al.
Published: (2023)

Asymptotically Unbiased Synthetic Control Methods by Moment Matching
by: Kato, Masahiro, et al.
Published: (2023)

Augmented balancing weights as linear regression
by: Bruns-Smith, David, et al.
Published: (2023)

Educational Effects in Mathematics: Conditional Average Treatment Effect depending on the Number of Treatments
by: Nagai, Tomoko, et al.
Published: (2024)

Formalising causal inference as prediction on a target population
by: Höltgen, Benedikt, et al.
Published: (2024)

Functional effects models: Accounting for preference heterogeneity in panel data with machine learning
by: Salvadé, Nicolas, et al.
Published: (2025)

Vector Copula Variational Inference and Dependent Block Posterior Approximations
by: Fu, Yu, et al.
Published: (2025)

Robust Matrix Estimation with Side Information
by: Agarwal, Anish, et al.
Published: (2026)

Fast Online Changepoint Detection
by: Ghezzi, Fabrizio, et al.
Published: (2024)

Regularizing Extrapolation in Causal Inference
by: Arbour, David, et al.
Published: (2025)

Estimation of Optimal Dynamic Treatment Assignment Rules under Policy Constraints
by: Sakaguchi, Shosei
Published: (2021)

A step towards the integration of machine learning and classic model-based survey methods
by: Żądło, Tomasz, et al.
Published: (2024)

Linear Multidimensional Regression with Interactive Fixed-Effects
by: Freeman, Hugo
Published: (2022)

HMM-LSTM Fusion Model for Economic Forecasting
by: Sivakumar, Guhan
Published: (2025)

Synthetic Potential Outcomes and Causal Mixture Identifiability
by: Mazaheri, Bijan, et al.
Published: (2024)

Re-examining Granger Causality with Causal Bayesian Networks and Reichenbachs Principles
by: Adedayo, S. A.
Published: (2025)

Calibration Strategies for Robust Causal Estimation: Theoretical and Empirical Insights on Propensity Score-Based Estimators
by: Klaassen, Sven, et al.
Published: (2025)