Inference for an Algorithmic Fairness-Accuracy Frontier
Fuente:
arXiv
Saved in:
| Main Authors: | Liu, Yiqi, Molinari, Francesca |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Forecasting Algorithms for Causal Inference with Panel Data
by: Goldin, Jacob, et al.
Published: (2022)
by: Goldin, Jacob, et al.
Published: (2022)
Information Based Inference in Models with Set-Valued Predictions and Misspecification
by: Kaido, Hiroaki, et al.
Published: (2024)
by: Kaido, Hiroaki, et al.
Published: (2024)
Stable Time Series Prediction of Enterprise Carbon Emissions Based on Causal Inference
by: Hong, Zitao, et al.
Published: (2026)
by: Hong, Zitao, et al.
Published: (2026)
Post Reinforcement Learning Inference
by: Syrgkanis, Vasilis, et al.
Published: (2023)
by: Syrgkanis, Vasilis, et al.
Published: (2023)
Estimation and Inference for Causal Functions with Multiway Clustered Data
by: Liu, Nan, et al.
Published: (2024)
by: Liu, Nan, et al.
Published: (2024)
A Projection-Based ARIMA Framework for Nonlinear Dynamics in Macroeconomic and Financial Time Series: Closed-Form Estimation and Rolling-Window Inference
by: Liu, Haojie, et al.
Published: (2025)
by: Liu, Haojie, et al.
Published: (2025)
Inference for Regression with Variables Generated by AI or Machine Learning
by: Battaglia, Laura, et al.
Published: (2024)
by: Battaglia, Laura, et al.
Published: (2024)
CAVIAR: Categorical-Variable Embeddings for Accurate and Robust Inference
by: Mukherjee, Anirban, et al.
Published: (2024)
by: Mukherjee, Anirban, et al.
Published: (2024)
Statistical Inference of Optimal Allocations I: Regularities and their Implications
by: Feng, Kai, et al.
Published: (2024)
by: Feng, Kai, et al.
Published: (2024)
Double Robust Bayesian Inference on Average Treatment Effects
by: Breunig, Christoph, et al.
Published: (2022)
by: Breunig, Christoph, et al.
Published: (2022)
Beating the Winner's Curse via Inference-Aware Policy Optimization
by: Bastani, Hamsa, et al.
Published: (2025)
by: Bastani, Hamsa, et al.
Published: (2025)
Neighborhood Adaptive Estimators for Causal Inference under Network Interference
by: Belloni, Alexandre, et al.
Published: (2022)
by: Belloni, Alexandre, et al.
Published: (2022)
A Unifying Framework for Robust and Efficient Inference with Unstructured Data
by: Carlson, Jacob, et al.
Published: (2025)
by: Carlson, Jacob, et al.
Published: (2025)
Profit-Aligned CATE Estimation: Reconciling Policy Learning and Inference
by: Timoshenko, Artem, et al.
Published: (2025)
by: Timoshenko, Artem, et al.
Published: (2025)
Algorithmic Compliance and Regulatory Loss in Digital Assets
by: Bhatt, Khem Raj, et al.
Published: (2026)
by: Bhatt, Khem Raj, et al.
Published: (2026)
Penalized GMM Framework for Inference on Functionals of Nonparametric Instrumental Variable Estimators
by: Bakhitov, Edvard
Published: (2026)
by: Bakhitov, Edvard
Published: (2026)
Double Machine Learning for Causal Inference under Shared-State Interference
by: Hays, Chris, et al.
Published: (2025)
by: Hays, Chris, et al.
Published: (2025)
Hyperparameter Tuning for Causal Inference with Double Machine Learning: A Simulation Study
by: Bach, Philipp, et al.
Published: (2024)
by: Bach, Philipp, et al.
Published: (2024)
Inference in Partially Linear Models under Dependent Data with Deep Neural Networks
by: Brown, Chad
Published: (2024)
by: Brown, Chad
Published: (2024)
Tight Non-asymptotic Inference via Sub-Gaussian Intrinsic Moment Norm
by: Zhang, Huiming, et al.
Published: (2023)
by: Zhang, Huiming, et al.
Published: (2023)
Regularizing Extrapolation in Causal Inference
by: Arbour, David, et al.
Published: (2025)
by: Arbour, David, et al.
Published: (2025)
Inference for Batched Adaptive Experiments
by: Kemper, Jan, et al.
Published: (2025)
by: Kemper, Jan, et al.
Published: (2025)
Applied Causal Inference Powered by ML and AI
by: Chernozhukov, Victor, et al.
Published: (2024)
by: Chernozhukov, Victor, et al.
Published: (2024)
LASSO Inference for High Dimensional Predictive Regressions
by: Gao, Zhan, et al.
Published: (2024)
by: Gao, Zhan, et al.
Published: (2024)
SLIM: Stochastic Learning and Inference in Overidentified Models
by: Chen, Xiaohong, et al.
Published: (2025)
by: Chen, Xiaohong, et al.
Published: (2025)
Improved Inference for CSDID Using the Cluster Jackknife
by: Karim, Sunny R., et al.
Published: (2026)
by: Karim, Sunny R., et al.
Published: (2026)
Doubly Robust Inference in Causal Latent Factor Models
by: Abadie, Alberto, et al.
Published: (2024)
by: Abadie, Alberto, et al.
Published: (2024)
A Causal Inference Framework for Data Rich Environments
by: Abadie, Alberto, et al.
Published: (2025)
by: Abadie, Alberto, et al.
Published: (2025)
Vector Copula Variational Inference and Dependent Block Posterior Approximations
by: Fu, Yu, et al.
Published: (2025)
by: Fu, Yu, et al.
Published: (2025)
Synthetic Combinations: A Causal Inference Framework for Combinatorial Interventions
by: Agarwal, Abhineet, et al.
Published: (2023)
by: Agarwal, Abhineet, et al.
Published: (2023)
Triple/Debiased Lasso for Statistical Inference of Conditional Average Treatment Effects
by: Kato, Masahiro
Published: (2024)
by: Kato, Masahiro
Published: (2024)
An Algorithm for Identifying Interpretable Subgroups With Elevated Treatment Effects
by: Chiu, Albert
Published: (2025)
by: Chiu, Albert
Published: (2025)
Amortized Inference for Correlated Discrete Choice Models via Equivariant Neural Networks
by: Huch, Easton, et al.
Published: (2026)
by: Huch, Easton, et al.
Published: (2026)
Long-term Causal Inference Under Persistent Confounding via Data Combination
by: Imbens, Guido, et al.
Published: (2022)
by: Imbens, Guido, et al.
Published: (2022)
A Cautionary Tale on Integrating Studies with Disparate Outcome Measures for Causal Inference
by: Parikh, Harsh, et al.
Published: (2025)
by: Parikh, Harsh, et al.
Published: (2025)
Cross-Validated Causal Inference: a Modern Method to Combine Experimental and Observational Data
by: Yang, Xuelin, et al.
Published: (2025)
by: Yang, Xuelin, et al.
Published: (2025)
Binary Choice under Asymmetric Loss in a Data-Rich Environment: Theory and an Application to Algorithmic Fairness
by: Babii, Andrii, et al.
Published: (2020)
by: Babii, Andrii, et al.
Published: (2020)
Robust Inference Methods for Latent Group Panel Models under Possible Group Non-Separation
by: Akgun, Oguzhan, et al.
Published: (2025)
by: Akgun, Oguzhan, et al.
Published: (2025)
Optimal Bias-Correction and Valid Inference in High-Dimensional Ridge Regression: A Closed-Form Solution
by: Gao, Zhaoxing, et al.
Published: (2024)
by: Gao, Zhaoxing, et al.
Published: (2024)
PPI-SVRG: Unifying Prediction-Powered Inference and Variance Reduction for Semi-Supervised Optimization
by: Ao, Ruicheng, et al.
Published: (2026)
by: Ao, Ruicheng, et al.
Published: (2026)
Similar Items
-
Forecasting Algorithms for Causal Inference with Panel Data
by: Goldin, Jacob, et al.
Published: (2022) -
Information Based Inference in Models with Set-Valued Predictions and Misspecification
by: Kaido, Hiroaki, et al.
Published: (2024) -
Stable Time Series Prediction of Enterprise Carbon Emissions Based on Causal Inference
by: Hong, Zitao, et al.
Published: (2026) -
Post Reinforcement Learning Inference
by: Syrgkanis, Vasilis, et al.
Published: (2023) -
Estimation and Inference for Causal Functions with Multiway Clustered Data
by: Liu, Nan, et al.
Published: (2024)