Imagen de Portada

Learning Decision Policies with Instrumental Variables through Double Machine Learning

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Shao, Daqian, Soleymani, Ashkan, Quinzan, Francesco, Kwiatkowska, Marta
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Double Machine Learning for Conditional Moment Restrictions: IV Regression, Proximal Causal Learning and Beyond
por: Shao, Daqian, et al.
Publicado: (2025)

Double Machine Learning Based Structure Identification from Temporal Data
por: Angelis, Emmanouil, et al.
Publicado: (2023)

Learning Optimal and Sample-Efficient Decision Policies with Guarantees
por: Shao, Daqian
Publicado: (2026)

STR-Cert: Robustness Certification for Deep Text Recognition on Deep Learning Pipelines and Vision Transformers
por: Shao, Daqian, et al.
Publicado: (2023)

Causal Imitation Learning under Expert-Observable and Expert-Unobservable Confounding
por: Shao, Daqian, et al.
Publicado: (2025)

Double Machine Learning of Continuous Treatment Effects with General Instrumental Variables
por: Chen, Shuyuan, et al.
Publicado: (2026)

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

Learning with Exact Invariances in Polynomial Time
por: Soleymani, Ashkan, et al.
Publicado: (2025)

Learning Counterfactually Invariant Predictors
por: Quinzan, Francesco, et al.
Publicado: (2022)

Pruning Cannot Hurt Robustness: Certified Trade-offs in Reinforcement Learning
por: Pedley, James, et al.
Publicado: (2025)

Faster Rates for No-Regret Learning in General Games via Cautious Optimism
por: Soleymani, Ashkan, et al.
Publicado: (2025)

Data Generation without Function Estimation
por: Daneshmand, Hadi, et al.
Publicado: (2025)

Learning to Ask: Decision Transformers for Adaptive Quantitative Group Testing
por: Soleymani, Mahdi, et al.
Publicado: (2025)

A Gaussian Comparison Theorem for Training Dynamics in Machine Learning
por: Panahi, Ashkan
Publicado: (2026)

Strategyproof Reinforcement Learning from Human Feedback
por: Buening, Thomas Kleine, et al.
Publicado: (2025)

Robust Reinforcement Learning from Human Feedback for Large Language Models Fine-Tuning
por: Ye, Kai, et al.
Publicado: (2025)

Addressing Instrument-Outcome Confounding in Mendelian Randomization through Representation Learning
por: Huang, Shimeng, et al.
Publicado: (2026)

Learning to Orchestrate Agents under Uncertainty
por: Oliver, Mary Chriselda Antony, et al.
Publicado: (2026)

Detecting Changes in Causal Dependence with Kernels and Copulas
por: Gavioli-Akilagun, Shakeel, et al.
Publicado: (2026)

Double Fairness Policy Learning: Integrating Action Fairness and Outcome Fairness in Decision-making
por: Bian, Zeyu, et al.
Publicado: (2026)

Cautious Optimism: A Meta-Algorithm for Near-Constant Regret in General Games
por: Soleymani, Ashkan, et al.
Publicado: (2025)

Confounded Causal Imitation Learning with Instrumental Variables
por: Zeng, Yan, et al.
Publicado: (2025)

Demystifying Spectral Feature Learning for Instrumental Variable Regression
por: Meunier, Dimitri, et al.
Publicado: (2025)

Learning Treatment Representations for Downstream Instrumental Variable Regression
por: Lin, Shiangyi, et al.
Publicado: (2025)

Instrumental Variable Value Iteration for Causal Offline Reinforcement Learning
por: Liao, Luofeng, et al.
Publicado: (2021)

Outcome-Aware Spectral Feature Learning for Instrumental Variable Regression
por: Meunier, Dimitri, et al.
Publicado: (2025)

AI Alignment in Medical Imaging: Unveiling Hidden Biases Through Counterfactual Analysis
por: Ma, Haroui, et al.
Publicado: (2025)

A Universal Class of Sharpness-Aware Minimization Algorithms
por: Tahmasebi, Behrooz, et al.
Publicado: (2024)

PreND: Enhancing Intrinsic Motivation in Reinforcement Learning through Pre-trained Network Distillation
por: Davoodabadi, Mohammadamin, et al.
Publicado: (2024)

MIBP-Cert: Certified Training against Data Perturbations with Mixed-Integer Bilinear Programs
por: Lorenz, Tobias, et al.
Publicado: (2024)

Nonparametric Instrumental Variable Regression through Stochastic Approximate Gradients
por: Fonseca, Yuri, et al.
Publicado: (2024)

IV-ICL: Bounding Causal Effects with Instrumental Variables via In-Context Learning
por: Balazadeh, Vahid, et al.
Publicado: (2026)

Model Averaging and Double Machine Learning
por: Ahrens, Achim, et al.
Publicado: (2024)

FullCert: Deterministic End-to-End Certification for Training and Inference of Neural Networks
por: Lorenz, Tobias, et al.
Publicado: (2024)

BASIS: Batchwise Advantage Estimation from Single-Rollout Information Sharing for LLM Reasoning
por: Gong, Shijin, et al.
Publicado: (2026)

Learning Deterministic Policies with Policy Gradients in Constrained Markov Decision Processes
por: Montenegro, Alessandro, et al.
Publicado: (2025)

Uncertainty-Aware Explanations Through Probabilistic Self-Explainable Neural Networks
por: Vadillo, Jon, et al.
Publicado: (2024)

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

Provable Preimage Under-Approximation for Neural Networks (Full Version)
por: Zhang, Xiyue, et al.
Publicado: (2023)

Identification and Debiased Learning of Causal Effects with General Instrumental Variables
por: Chen, Shuyuan, et al.
Publicado: (2025)