Alan Mishler
  • About
  • Experience
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  • Papers
  • Publications
    • Auditing and Enforcing Conditional Fairness via Optimal Transport
    • Monty Hall and Score Optimization in Conformal Prediction to Improve LLM performance in Multi-choice Question Answering
    • Semiparametric Efficient Inference in Adaptive Experiments
    • FairWASP: Fast and Optimal Fair Wasserstein Pre-processing
    • Hyper-parameter Tuning for Fair Classification without Sensitive Attribute Access
    • Active Learning with Missing Not At Random Outcomes
    • Fairness via In-Processing in the Over-parameterized Regime: A Cautionary Tale with MinDiff Loss
    • Counterfactual Mean-Variance Optimization
    • FADE: FAir Double Ensemble Learning for Observable and Counterfactual Outcomes
    • Fair When Trained, Unfair When Deployed: Observable Fairness Measures are Unstable in Performative Prediction Settings
    • Flexible Group Fairness Metrics for Survival Analysis
    • Challenges in Obtaining Valid Causal Effect Estimates with Machine Learning Algorithms
    • Comment on “Statistical Modeling: The Two Cultures” by Leo Breiman
    • Fairness in Risk Assessment Instruments: Post-Processing to Achieve Counterfactual Equalized Odds
    • When the Oracle Misleads: Modeling the Consequences of Using Observable Rather than Potential Outcomes in Risk Assessment Instruments
    • Memory and Language Improvements following Cognitive Control Training
    • Modeling Triage Decision Making
    • The bilingual advantage: Conflict monitoring, cognitive control, and garden-path recovery
    • Contrasting interference profiles for agreement and anaphora: Experimental and modeling evidence
    • Evidence for language transfer leading to a perceptual advantage for non-native listeners
  • Projects

Counterfactual Mean-Variance Optimization

Jan 1, 2022·
Kwangho Kim
Alan Mishler
Alan Mishler
,
José Zubizarreta
· 0 min read
Cite arXiv
Type
Journal article
Last updated on Jan 1, 2022
Alan Mishler
Authors
Alan Mishler
AI Research Lead/VP
← Fairness via In-Processing in the Over-parameterized Regime: A Cautionary Tale with MinDiff Loss Jan 1, 2023
FADE: FAir Double Ensemble Learning for Observable and Counterfactual Outcomes Jan 1, 2022 →

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