Ustun, Berk

29 publications

ICLR 2025 Concept Bottleneck Large Language Models Chung-En Sun, Tuomas Oikarinen, Berk Ustun, Tsui-Wei Weng

ICLR 2025 Feature Responsiveness Scores: Model-Agnostic Explanations for Recourse Seung Hyun Cheon, Anneke Wernerfelt, Sorelle Friedler, Berk Ustun

ICLR 2025 Learning Under Temporal Label Noise Sujay Nagaraj, Walter Gerych, Sana Tonekaboni, Anna Goldenberg, Berk Ustun, Thomas Hartvigsen

ICLR 2025 Regretful Decisions Under Label Noise Sujay Nagaraj, Yang Liu, Flavio Calmon, Berk Ustun

ICML 2025 Selective Preference Aggregation Shreyas Kadekodi, Hayden Mctavish, Berk Ustun

ICML 2025 Understanding Fixed Predictions via Confined Regions Connor Lawless, Tsui-Wei Weng, Berk Ustun, Madeleine Udell

ICLR 2024 Classification with Conceptual Safeguards Hailey Joren, Charles Thomas Marx, Berk Ustun

NeurIPSW 2024 Feature Responsiveness Scores: Model-Agnostic Explanations for Recourse Seung Hyun Cheon, Anneke Wernerfelt, Sorelle Friedler, Berk Ustun

NeurIPSW 2024 Learning from Personal Preferences Kelly Jiang, Berk Ustun, Jessica Hullman

NeurIPSW 2024 On Interpretability and Overreliance Julian Skirzynski, Elena Glassman, Berk Ustun

ICLR 2024 Prediction Without Preclusion: Recourse Verification with Reachable Sets Avni Kothari, Bogdan Kulynych, Tsui-Wei Weng, Berk Ustun

AAAI 2024 Providing Fair Recourse over Plausible Groups Jayanth Yetukuri, Ian Hardy, Yevgeniy Vorobeychik, Berk Ustun, Yang Liu

NeurIPSW 2024 Selective Preference Aggregation Shreyas Kadekodi, Hayden McTavish, Berk Ustun

NeurIPSW 2024 Selective Preference Aggregation Shreyas Kadekodi, Hayden McTavish, Berk Ustun

NeurIPSW 2024 Time Series Under Temporal Label Noise Sujay Nagaraj, Walter Gerych, Sana Tonekaboni, Anna Goldenberg, Berk Ustun, Thomas Hartvigsen

NeurIPS 2023 Participatory Personalization in Classification Hailey Joren, Chirag Nagpal, Katherine A. Heller, Berk Ustun

ICMLW 2023 Participatory Personalization in Classification Hailey Joren, Chirag Nagpal, Katherine A Heller, Berk Ustun

AAAI 2023 Predictive Multiplicity in Probabilistic Classification Jamelle Watson-Daniels, David C. Parkes, Berk Ustun

ICML 2023 When Personalization Harms Performance: Reconsidering the Use of Group Attributes in Prediction Vinith Menon Suriyakumar, Marzyeh Ghassemi, Berk Ustun

NeurIPS 2022 On the Epistemic Limits of Personalized Prediction Lucas Monteiro Paes, Carol Long, Berk Ustun, Flavio Calmon

NeurIPSW 2022 Participatory Systems for Personalized Prediction Hailey Joren, Chirag Nagpal, Katherine A Heller, Berk Ustun

NeurIPSW 2022 Participatory Systems for Personalized Prediction Hailey Joren, Chirag Nagpal, Katherine A Heller, Berk Ustun

NeurIPSW 2022 When Personalization Harms: Reconsidering the Use of Group Attributes of Prediction Vinith Menon Suriyakumar, Marzyeh Ghassemi, Berk Ustun

NeurIPS 2021 Learning Optimal Predictive Checklists Haoran Zhang, Quaid D. Morris, Berk Ustun, Marzyeh Ghassemi

ICML 2020 Predictive Multiplicity in Classification Charles Marx, Flavio Calmon, Berk Ustun

ICML 2019 Fairness Without Harm: Decoupled Classifiers with Preference Guarantees Berk Ustun, Yang Liu, David Parkes

JMLR 2019 Learning Optimized Risk Scores Berk Ustun, Cynthia Rudin

ICML 2019 Repairing Without Retraining: Avoiding Disparate Impact with Counterfactual Distributions Hao Wang, Berk Ustun, Flavio Calmon

MLJ 2016 Supersparse Linear Integer Models for Optimized Medical Scoring Systems Berk Ustun, Cynthia Rudin