prediction model

Fairness under Graph Uncertainty: Achieving Interventional Fairness with Partially Known Causal Graphs over Clusters of Variables UAI 2026 Another Approach to Agreement Measurement and Prediction with Emotion Annotations ACL 2025 Minimalistic Predictions for Online Class Constraint Scheduling ICLR 2025 Reproducing the Argument Quality Prediction of Project Debater ACL 2025 UP-VLA: A Unified Understanding and Prediction Model for Embodied Agent ICML 2025 Contextual Feature Selection with Conditional Stochastic Gates ICML 2024 Ensuring Fairness Stability for Disentangling Social Inequality in Access to Education: the FAiRDAS General Method IJCAI 2024 Evaluating a 3-factor listener model for prediction of speech intelligibility to hearing-impaired listeners Interspeech 2024 FRAPPÉ: A Group Fairness Framework for Post-Processing Everything ICML 2024 Prediction-powered Generalization of Causal Inferences ICML 2024 Provable Detection of Propagating Sampling Bias in Prediction Models AAAI 2023 Selection by Prediction with Conformal p-values JMLR 2023 Anticipating Performativity by Predicting from Predictions NeurIPS 2022 DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation AAAI 2022 MBI-Net: A Non-Intrusive Multi-Branched Speech Intelligibility Prediction Model for Hearing Aids Interspeech 2022 Using time-series privileged information for provably efficient learning of prediction models AISTATS 2022 Why predicting risk can’t identify ‘risk factors’: empirical assessment of model stability in machine learning across observational health databases MLHC 2022 Interventions Recommendation: Professionals’ Observations Analysis in Special Needs Education EACL 2021 Model updating after interventions paradoxically introduces bias AISTATS 2021 Determining Event Outcomes: The Case of #fail EMNLP 2020 How does This Interaction Affect Me? Interpretable Attribution for Feature Interactions NeurIPS 2020 Measuring Forecasting Skill from Text ACL 2020 Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Control ICML 2020 All Models are Wrong, but Many are Useful: Learning a Variable's Importance by Studying an Entire Class of Prediction Models Simultaneously JMLR 2019 Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks MLHC 2019