Berk Ustun

ORCID

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 34

Top Venues

Massachusetts Institute of Technology, Cambridge, USA (PHD)

Education History

Massachusetts Institute of Technology, Cambridge, USA

PHD

Publications

Jayanth Yetukuri, Ian Hardy, Yevgeniy Vorobeychik, Berk Ustun, Yang Liu
Providing Fair Recourse over Plausible Groups. AAAI (2024)
Hailey Joren, Charles T. Marx, Berk Ustun
Classification with Conceptual Safeguards. ICLR (2024)
Talia B. Gillis, Vitaly Meursault, Berk Ustun
Operationalizing the Search for Less Discriminatory Alternatives in Fair Lending. FAccT (2024)
Sejoon Oh, Berk Ustun, Julian J. McAuley, Srijan Kumar
FINEST: Stabilizing Recommendations by Rank-Preserving Fine-Tuning. CoRR (2024)
Avni Kothari, Bogdan Kulynych, Tsui-Wei Weng, Berk Ustun
Prediction without Preclusion: Recourse Verification with Reachable Sets. ICLR (2024)
Hyewon Jeong, Sarah Jabbour, Yuzhe Yang, Rahul Thapa, Hussein Mozannar, William Jongwon Han, Nikita Mehandru, Michael Wornow, Vladislav Lialin, Xin Liu, Alejandro Lozano, Jiacheng Zhu, Rafal Dariusz Kocielnik, Keith Harrigian, Haoran Zhang, Edward Lee, Milos Vukadinovic, Aparna Balagopalan, Vincent Jeanselme, Katherine Matton, Ilker Demirel, Jason A. Fries, Parisa Rashidi, Brett K. Beaulieu-Jones, Xuhai "Orson" Xu, Matthew B. A. McDermott, Tristan Naumann, Monica Agrawal, Marinka Zitnik, Berk Ustun, Edward Choi, Kristen Yeom, Gamze Gürsoy, Marzyeh Ghassemi, Emma Pierson, George H. Chen, Sanjat Kanjilal, Michael Oberst, Linying Zhang, Harvineet Singh, Tom Hartvigsen, Helen Zhou, Chinasa T. Okolo
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium. CoRR (2024)
Sujay Nagaraj, Walter Gerych, Sana Tonekaboni, Anna Goldenberg, Berk Ustun, Thomas Hartvigsen
Learning from Time Series under Temporal Label Noise. CoRR (2024)
Jamelle Watson-Daniels, Flávio du Pin Calmon, Alexander D'Amour, Carol Xuan Long, David C. Parkes, Berk Ustun
Predictive Churn with the Set of Good Models. CoRR (2024)
Hailey James, Chirag Nagpal, Katherine A. Heller, Berk Ustun
Participatory Systems for Personalized Prediction. CoRR (2023)
Jennifer Chien, Margaret E. Roberts, Berk Ustun
Algorithmic Censoring in Dynamic Learning Systems. EAAMO (2023)
Hailey Joren, Chirag Nagpal, Katherine A. Heller, Berk Ustun
Participatory Personalization in Classification. NeurIPS (2023)
Jennifer Chien, Margaret E. Roberts, Berk Ustun
Algorithmic Censoring in Dynamic Learning Systems. CoRR (2023)
Jamelle Watson-Daniels, David C. Parkes, Berk Ustun
Predictive Multiplicity in Probabilistic Classification. AAAI (2023)
Vinith Menon Suriyakumar, Marzyeh Ghassemi, Berk Ustun
When Personalization Harms Performance: Reconsidering the Use of Group Attributes in Prediction. ICML (2023)
Avni Kothari, Bogdan Kulynych, Tsui-Wei Weng, Berk Ustun
Prediction without Preclusion: Recourse Verification with Reachable Sets. CoRR (2023)
Jamelle Watson-Daniels, David C. Parkes, Berk Ustun
Predictive Multiplicity in Probabilistic Classification. CoRR (2022)
Vinith M. Suriyakumar, Marzyeh Ghassemi, Berk Ustun
When Personalization Harms: Reconsidering the Use of Group Attributes in Prediction. CoRR (2022)
Sejoon Oh, Berk Ustun, Julian J. McAuley, Srijan Kumar
Rank List Sensitivity of Recommender Systems to Interaction Perturbations. CIKM (2022)
Lucas Monteiro Paes, Carol Long, Berk Ustun, Flávio P. Calmon
On the Epistemic Limits of Personalized Prediction. NeurIPS (2022)
Haoran Zhang, Quaid Morris, Berk Ustun, Marzyeh Ghassemi
Learning Optimal Predictive Checklists. CoRR (2021)
Haoran Zhang, Quaid Morris, Berk Ustun, Marzyeh Ghassemi
Learning Optimal Predictive Checklists. NeurIPS (2021)
Charles T. Marx, Flávio P. Calmon, Berk Ustun
Predictive Multiplicity in Classification. ICML (2020)
Berk Ustun, Alexander Spangher, Yang Liu
Actionable Recourse in Linear Classification. FAT (2019)
Berk Ustun, Yang Liu, David C. Parkes
Fairness without Harm: Decoupled Classifiers with Preference Guarantees. ICML (2019)
Hao Wang, Berk Ustun, Flávio P. Calmon
Repairing without Retraining: Avoiding Disparate Impact with Counterfactual Distributions. ICML (2019)
Charles T. Marx, Flávio du Pin Calmon, Berk Ustun
Predictive Multiplicity in Classification. CoRR (2019)
Berk Ustun, Cynthia Rudin
Learning Optimized Risk Scores. J. Mach. Learn. Res. 20 (2019)
Hao Wang, Berk Ustun, Flávio P. Calmon
Repairing without Retraining: Avoiding Disparate Impact with Counterfactual Distributions. CoRR (2019)
Cynthia Rudin, Berk Ustun
Optimized Scoring Systems: Toward Trust in Machine Learning for Healthcare and Criminal Justice. Interfaces 48 (5) (2018)
Hao Wang, Berk Ustun, Flávio du Pin Calmon
On the Direction of Discrimination: An Information-Theoretic Analysis of Disparate Impact in Machine Learning. ISIT (2018)
Berk Ustun, Alexander Spangher, Yang Liu
Actionable Recourse in Linear Classification. CoRR (2018)
Hao Wang, Berk Ustun, Flávio du Pin Calmon
On the Direction of Discrimination: An Information-Theoretic Analysis of Disparate Impact in Machine Learning. CoRR (2018)
Berk Ustun, Cynthia Rudin
Optimized Risk Scores. KDD (2017)
Berk Ustun, Cynthia Rudin
Supersparse linear integer models for optimized medical scoring systems. Mach. Learn. 102 (3) (2016)
Berk Ustun, Cynthia Rudin
Supersparse Linear Integer Models for Optimized Medical Scoring Systems. CoRR (2015)
Panos Parpas, Berk Ustun, Mort Webster, Quang Kha Tran
Importance Sampling in Stochastic Programming: A Markov Chain Monte Carlo Approach. INFORMS J. Comput. 27 (2) (2015)
Berk Ustun, Cynthia Rudin
Methods and Models for Interpretable Linear Classification. CoRR (2014)
Berk Ustun, Stefano Tracà, Cynthia Rudin
Supersparse Linear Integer Models for Predictive Scoring Systems. AAAI (Late-Breaking Developments) (2013)

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Publication Activity (10 Years)

Top Topics

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Berk Ustun