Copertina

A Unifying Framework for Robust and Efficient Inference with Unstructured Data

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Carlson, Jacob, Dell, Melissa
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Econometrics Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Making Interpretable Discoveries from Unstructured Data: A High-Dimensional Multiple Hypothesis Testing Approach
di: Carlson, Jacob
Pubblicazione: (2025)

From Unstructured Data to Demand Counterfactuals: Theory and Practice
di: Christensen, Timothy, et al.
Pubblicazione: (2026)

Forecasting Algorithms for Causal Inference with Panel Data
di: Goldin, Jacob, et al.
Pubblicazione: (2022)

Copyright and Competition: Estimating Supply and Demand with Unstructured Data
di: Han, Sukjin, et al.
Pubblicazione: (2025)

A Causal Inference Framework for Data Rich Environments
di: Abadie, Alberto, et al.
Pubblicazione: (2025)

CAVIAR: Categorical-Variable Embeddings for Accurate and Robust Inference
di: Mukherjee, Anirban, et al.
Pubblicazione: (2024)

Penalized GMM Framework for Inference on Functionals of Nonparametric Instrumental Variable Estimators
di: Bakhitov, Edvard
Pubblicazione: (2026)

Doubly Robust Inference in Causal Latent Factor Models
di: Abadie, Alberto, et al.
Pubblicazione: (2024)

Double Robust Bayesian Inference on Average Treatment Effects
di: Breunig, Christoph, et al.
Pubblicazione: (2022)

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

Inference in Partially Linear Models under Dependent Data with Deep Neural Networks
di: Brown, Chad
Pubblicazione: (2024)

A Projection-Based ARIMA Framework for Nonlinear Dynamics in Macroeconomic and Financial Time Series: Closed-Form Estimation and Rolling-Window Inference
di: Liu, Haojie, et al.
Pubblicazione: (2025)

Estimation and Inference for Causal Functions with Multiway Clustered Data
di: Liu, Nan, et al.
Pubblicazione: (2024)

Multi-Band Variable-Lag Granger Causality: A Unified Framework for Causal Time Series Inference across Frequencies
di: Sookkongwaree, Chakattrai, et al.
Pubblicazione: (2025)

Robust Inference Methods for Latent Group Panel Models under Possible Group Non-Separation
di: Akgun, Oguzhan, et al.
Pubblicazione: (2025)

Spatially Robust Inference with Predicted and Missing at Random Labels
di: Salerno, Stephen, et al.
Pubblicazione: (2026)

Post Reinforcement Learning Inference
di: Syrgkanis, Vasilis, et al.
Pubblicazione: (2023)

Inference for an Algorithmic Fairness-Accuracy Frontier
di: Liu, Yiqi, et al.
Pubblicazione: (2024)

PPI-SVRG: Unifying Prediction-Powered Inference and Variance Reduction for Semi-Supervised Optimization
di: Ao, Ruicheng, et al.
Pubblicazione: (2026)

Long-term Causal Inference Under Persistent Confounding via Data Combination
di: Imbens, Guido, et al.
Pubblicazione: (2022)

A Unified Framework for Estimation of High-dimensional Conditional Factor Models
di: Chen, Qihui
Pubblicazione: (2022)

Hyperparameter Tuning for Causal Inference with Double Machine Learning: A Simulation Study
di: Bach, Philipp, et al.
Pubblicazione: (2024)

Optimizing Adaptive Experiments: A Unified Approach to Regret Minimization and Best-Arm Identification
di: Qin, Chao, et al.
Pubblicazione: (2024)

Cross-Validated Causal Inference: a Modern Method to Combine Experimental and Observational Data
di: Yang, Xuelin, et al.
Pubblicazione: (2025)

Inference for Regression with Variables Generated by AI or Machine Learning
di: Battaglia, Laura, et al.
Pubblicazione: (2024)

Statistical Inference of Optimal Allocations I: Regularities and their Implications
di: Feng, Kai, et al.
Pubblicazione: (2024)

Beating the Winner's Curse via Inference-Aware Policy Optimization
di: Bastani, Hamsa, et al.
Pubblicazione: (2025)

Profit-Aligned CATE Estimation: Reconciling Policy Learning and Inference
di: Timoshenko, Artem, et al.
Pubblicazione: (2025)

Neighborhood Adaptive Estimators for Causal Inference under Network Interference
di: Belloni, Alexandre, et al.
Pubblicazione: (2022)

Double Machine Learning for Causal Inference under Shared-State Interference
di: Hays, Chris, et al.
Pubblicazione: (2025)

Stable Time Series Prediction of Enterprise Carbon Emissions Based on Causal Inference
di: Hong, Zitao, et al.
Pubblicazione: (2026)

Tight Non-asymptotic Inference via Sub-Gaussian Intrinsic Moment Norm
di: Zhang, Huiming, et al.
Pubblicazione: (2023)

Debiased Nonparametric Regression for Statistical Inference and Distributionally Robustness
di: Kato, Masahiro
Pubblicazione: (2024)

Regularizing Extrapolation in Causal Inference
di: Arbour, David, et al.
Pubblicazione: (2025)

Inference for Batched Adaptive Experiments
di: Kemper, Jan, et al.
Pubblicazione: (2025)

A Unified Theory for Causal Inference: Direct Debiased Machine Learning via Bregman-Riesz Regression
di: Kato, Masahiro
Pubblicazione: (2025)

CAREER: A Foundation Model for Labor Sequence Data
di: Vafa, Keyon, et al.
Pubblicazione: (2022)

A Granular Framework for Construction Material Price Forecasting: Econometric and Machine-Learning Approaches
di: Lyu, Boge, et al.
Pubblicazione: (2025)

SLIM: Stochastic Learning and Inference in Overidentified Models
di: Chen, Xiaohong, et al.
Pubblicazione: (2025)

Applied Causal Inference Powered by ML and AI
di: Chernozhukov, Victor, et al.
Pubblicazione: (2024)