Cover Image

A Decision Theoretic Perspective on Artificial Superintelligence: Coping with Missing Data Problems in Prediction and Treatment Choice

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Dominitz, Jeff, Manski, Charles F.
Format:	Preprint
Published:	2025
Subjects:	Econometrics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Limit Regret in Binary Treatment Choice with Misspecified Plug-In Predictors and Decision Thresholds
by: Dominitz, Jeff, et al.
Published: (2025)

Comprehensive OOS Evaluation of Predictive Algorithms with Statistical Decision Theory
by: Dominitz, Jeff, et al.
Published: (2024)

Using Total Margin of Error to Account for Non-Sampling Error in Election Polls: The Case of Nonresponse
by: Dominitz, Jeff, et al.
Published: (2024)

Coping with Inductive Risk When Theories are Underdetermined: Decision Making with Partial Identification
by: Manski, Charles F.
Published: (2026)

Identification and Statistical Decision Theory
by: Manski, Charles F.
Published: (2022)

Partial Identification of Mean Achievement in ILSA Studies with Multi-Stage Stratified Sample Design and Student Non-Participation
by: Cortes, Diego, et al.
Published: (2025)

Using Ordinal Voting to Compare the Utilitarian Welfare of a Status Quo and A Proposed Policy: A Simple Nonparametric Analysis
by: Manski, Charles F.
Published: (2024)

Prediction with Differential Covariate Classification: Illustrated by Covariate Classification in Medical Risk Assessment
by: Venkataramani, Atheendar S., et al.
Published: (2025)

Utilitarian or Quantile-Welfare Evaluation of Social Welfare? With Application to Health Cost-Effectiveness Analysis
by: Manski, Charles F., et al.
Published: (2025)

Decision Theory for Treatment Choice Problems with Partial Identification
by: Olea, José Luis Montiel, et al.
Published: (2023)

The Subtlety of Optimal Paternalism in a Population with Bounded Rationality
by: Manski, Charles F., et al.
Published: (2024)

Sequential Decision Problems with Missing Feedback
by: Palomba, Filippo
Published: (2025)

Robust Bayes Treatment Choice with Partial Identification
by: Fernández, Andrés Aradillas, et al.
Published: (2024)

Treatment Choice with Nonlinear Regret
by: Kitagawa, Toru, et al.
Published: (2022)

Evidence Aggregation for Treatment Choice
by: Ishihara, Takuya, et al.
Published: (2021)

Shrinkage Methods for Treatment Choice
by: Ishihara, Takuya, et al.
Published: (2022)

Nonparametric Treatment Effect Identification in School Choice
by: Chen, Jiafeng
Published: (2021)

Rethinking Distributional IVs: KAN-Powered D-IV-LATE & Model Choice
by: Shaw, Charles
Published: (2025)

Using SVM to Estimate and Predict Binary Choice Models
by: Chang, Yoosoon, et al.
Published: (2026)

Epsilon-Minimax Solutions of Statistical Decision Problems
by: Fernández, Andrés Aradillas, et al.
Published: (2025)

A Bayesian Perspective on the Maximum Score Problem
by: Walker, Christopher D.
Published: (2024)

Bounds on Average Effects in Discrete Choice Panel Data Models
by: Pakel, Cavit, et al.
Published: (2023)

Semiparametric Estimation of Dynamic Binary Choice Panel Data Models
by: Ouyang, Fu, et al.
Published: (2022)

Revisiting Panel Data Discrete Choice Models with Lagged Dependent Variables
by: Dobronyi, Christopher R., et al.
Published: (2023)

Distributional Change in Ordinal Data with Missing Observations: Minimal Mobility and Partial Identification
by: Tabri, Rami V.
Published: (2026)

Enabling Decision-Making with the Modified Causal Forest: Policy Trees for Treatment Assignment
by: Bodory, Hugo, et al.
Published: (2024)

Dynamic Discrete-Continuous Choice Models: Identification and Conditional Choice Probability Estimation
by: Bruneel-Zupanc, Christophe
Published: (2025)

Predicting the Distribution of Treatment Effects: A Covariate-Adjustment Approach
by: Fava, Bruno
Published: (2024)

Conditional Choice Probability Estimation of Dynamic Discrete Choice Models with 2-period Finite Dependence
by: Hao, Yu, et al.
Published: (2024)

Reinforcement Learning Based Computationally Efficient Conditional Choice Simulation Estimation of Dynamic Discrete Choice Models
by: Khwaja, Ahmed, et al.
Published: (2026)

Optimal Policy Choices Under Uncertainty
by: Moon, Sarah
Published: (2025)

Semiparametric Discrete Choice Models for Bundles
by: Ouyang, Fu, et al.
Published: (2023)

Semiparametric Discrete Choice Models for Bundles
by: Ouyang, Fu, et al.
Published: (2023)

Spillovers of Program Benefits with Missing Network Links
by: Zhang, Lina
Published: (2020)

Data-Driven Policy Learning for Continuous Treatments
by: Ai, Chunrong, et al.
Published: (2024)

Mobility Behaviour of Immigrants in Canada: Analyzing Mode Choice Using GPS Panel Data and Mixed Logit Models
by: Alsaleh, Tareq, et al.
Published: (2026)

A Simple and Powerful Diagnostic Test for Binary Choice Models
by: Ji, Ting, et al.
Published: (2026)

Constrained Recursive Logit for Route Choice Analysis
by: Tran, Hung, et al.
Published: (2025)

Sensitivity Analysis for Dynamic Discrete Choice Models
by: Lau, Chun Pong
Published: (2024)

Changes-in-Changes for Ordered Choice Models with Underreporting
by: Gutknecht, Daniel, et al.
Published: (2024)