Berk Ustun - RankMe

57 papers A* 18A 1B 1Journal 31Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Bridging Prediction and Intervention Problems in Social Systems. CoRR Lydia T. Liu, Inioluwa Deborah Raji, Angela Zhou, Luke Guerdan, Jessica Hullman, Daniel Malinsky, Bryan Wilder, Simone Zhang, Hammaad Adam, Amanda Coston, Benjamin Laufer, Ezinne Nwankwo, Michael Zanger-Tishler, Eli Ben-Michael, Solon Barocas, Avi Feller, Marissa Gerchick, Talia Gillis, Shion Guha, Daniel E. Ho, Lily Hu, Kosuke Imai, Sayash Kapoor, Joshua Loftus, Razieh Nabi, Arvind Narayanan, Ben Recht, Juan Carlos Perdomo, Matthew J. Salganik, Mark P. Sendak, Alexander Tolbert, Berk Ustun, Suresh Venkatasubramanian, Angelina Wang, Ashia Wilson
2025	A*	`conf`	Concept Bottleneck Large Language Models. ICLR Chung-En Sun, Tuomas P. Oikarinen, Berk Ustun, Tsui-Wei Weng
2025	—	`conf`	Discrimination Exposed? On the Reliability of Explanations for Discrimination Detection. FAccT Julian Skirzynski, David Danks, Berk Ustun
2025	J	`jnl`	Explanations are a means to an end. CoRR Jessica Hullman, Ziyang Guo, Berk Ustun
2025	A*	`conf`	Feature Responsiveness Scores: Model-Agnostic Explanations for Recourse. ICLR Seung Hyun Cheon, Anneke Wernerfelt, Sorelle A. Friedler, Berk Ustun
2025	A*	`conf`	Learning under Temporal Label Noise. ICLR Sujay Nagaraj, Walter Gerych, Sana Tonekaboni, Anna Goldenberg, Berk Ustun, Thomas Hartvigsen
2025	J	`jnl`	Observational Multiplicity. CoRR Erin George, Deanna Needell, Berk Ustun
2025	A*	`conf`	Regretful Decisions under Label Noise. ICLR Sujay Nagaraj, Yang Liu, Flávio P. Calmon, Berk Ustun
2025	J	`jnl`	Regretful Decisions under Label Noise. CoRR Sujay Nagaraj, Yang Liu, Flávio P. Calmon, Berk Ustun
2025	A*	`conf`	Selective Preference Aggregation. ICML Shreyas Kadekodi, Hayden McTavish, Berk Ustun
2025	J	`jnl`	Statistical Inference for Responsiveness Verification. CoRR Seung Hyun Cheon, Meredith Stewart, Bogdan Kulynych, Tsui-Wei Weng, Berk Ustun
2025	A*	`conf`	Understanding Fixed Predictions via Confined Regions. ICML Connor Lawless, Tsui-Wei Weng, Berk Ustun, Madeleine Udell
2025	J	`jnl`	Understanding Fixed Predictions via Confined Regions. CoRR Connor Lawless, Tsui-Wei Weng, Berk Ustun, Madeleine Udell
2024	A*	`conf`	Classification with Conceptual Safeguards. ICLR Hailey Joren, Charles T. Marx, Berk Ustun
2024	J	`jnl`	Classification with Conceptual Safeguards. CoRR Hailey Joren, Charles T. Marx, Berk Ustun
2024	J	`jnl`	Concept Bottleneck Large Language Models. CoRR Chung-En Sun, Tuomas P. Oikarinen, Berk Ustun, Tsui-Wei Weng
2024	J	`jnl`	FINEST: Stabilizing Recommendations by Rank-Preserving Fine-Tuning. CoRR Sejoon Oh, Berk Ustun, Julian J. McAuley, Srijan Kumar
2024	J	`jnl`	FINEST: Stabilizing Recommendations by Rank-Preserving Fine-Tuning. ACM Trans. Knowl. Discov. Data Sejoon Oh, Berk Ustun, Julian J. McAuley, Srijan Kumar
2024	J	`jnl`	Feature Responsiveness Scores: Model-Agnostic Explanations for Recourse. CoRR Seung Hyun Cheon, Anneke Wernerfelt, Sorelle A. Friedler, Berk Ustun
2024	J	`jnl`	Guidance for unbiased predictive information for healthcare decision-making and equity (GUIDE): considerations when race may be a prognostic factor. npj Digit. Medicine Keren Ladin, John Cuddeback, O. Kenrik Duru, Sharad Goel, William Harvey, Jinny G. Park, Jessica K. Paulus, Joyce Sackey, Richard Sharp, Ewout W. Steyerberg, Berk Ustun, David van Klaveren, Saul N. Weingart, David M. Kent
2024	J	`jnl`	Learning from Time Series under Temporal Label Noise. CoRR Sujay Nagaraj, Walter Gerych, Sana Tonekaboni, Anna Goldenberg, Berk Ustun, Thomas Hartvigsen
2024	—	`conf`	Operationalizing the Search for Less Discriminatory Alternatives in Fair Lending. FAccT Talia B. Gillis, Vitaly Meursault, Berk Ustun
2024	A*	`conf`	Prediction without Preclusion: Recourse Verification with Reachable Sets. ICLR Avni Kothari, Bogdan Kulynych, Tsui-Wei Weng, Berk Ustun
2024	J	`jnl`	Predictive Churn with the Set of Good Models. CoRR Jamelle Watson-Daniels, Flávio du Pin Calmon, Alexander D'Amour, Carol Xuan Long, David C. Parkes, Berk Ustun
2024	A*	`conf`	Providing Fair Recourse over Plausible Groups. AAAI Jayanth Yetukuri, Ian Hardy, Yevgeniy Vorobeychik, Berk Ustun, Yang Liu
2024	J	`jnl`	Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium. CoRR 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
2023	—	`conf`	Algorithmic Censoring in Dynamic Learning Systems. EAAMO Jennifer Chien, Margaret E. Roberts, Berk Ustun
2023	J	`jnl`	Algorithmic Censoring in Dynamic Learning Systems. CoRR Jennifer Chien, Margaret E. Roberts, Berk Ustun
2023	A*	`conf`	Participatory Personalization in Classification. NeurIPS Hailey Joren, Chirag Nagpal, Katherine A. Heller, Berk Ustun
2023	J	`jnl`	Participatory Systems for Personalized Prediction. CoRR Hailey James, Chirag Nagpal, Katherine A. Heller, Berk Ustun
2023	J	`jnl`	Prediction without Preclusion: Recourse Verification with Reachable Sets. CoRR Avni Kothari, Bogdan Kulynych, Tsui-Wei Weng, Berk Ustun
2023	A*	`conf`	Predictive Multiplicity in Probabilistic Classification. AAAI Jamelle Watson-Daniels, David C. Parkes, Berk Ustun
2023	A*	`conf`	When Personalization Harms Performance: Reconsidering the Use of Group Attributes in Prediction. ICML Vinith Menon Suriyakumar, Marzyeh Ghassemi, Berk Ustun
2022	A*	`conf`	On the Epistemic Limits of Personalized Prediction. NeurIPS Lucas Monteiro Paes, Carol Xuan Long, Berk Ustun, Flávio P. Calmon
2022	J	`jnl`	Predictive Multiplicity in Probabilistic Classification. CoRR Jamelle Watson-Daniels, David C. Parkes, Berk Ustun
2022	A	`conf`	Rank List Sensitivity of Recommender Systems to Interaction Perturbations. CIKM Sejoon Oh, Berk Ustun, Julian J. McAuley, Srijan Kumar
2022	J	`jnl`	When Personalization Harms: Reconsidering the Use of Group Attributes in Prediction. CoRR Vinith M. Suriyakumar, Marzyeh Ghassemi, Berk Ustun
2021	A*	`conf`	Learning Optimal Predictive Checklists. NeurIPS Haoran Zhang, Quaid Morris, Berk Ustun, Marzyeh Ghassemi
2021	J	`jnl`	Learning Optimal Predictive Checklists. CoRR Haoran Zhang, Quaid Morris, Berk Ustun, Marzyeh Ghassemi
2020	A*	`conf`	Predictive Multiplicity in Classification. ICML Charles T. Marx, Flávio P. Calmon, Berk Ustun
2019	—	`conf`	Actionable Recourse in Linear Classification. FAT Berk Ustun, Alexander Spangher, Yang Liu
2019	A*	`conf`	Fairness without Harm: Decoupled Classifiers with Preference Guarantees. ICML Berk Ustun, Yang Liu, David C. Parkes
2019	J	`jnl`	Learning Optimized Risk Scores. J. Mach. Learn. Res. Berk Ustun, Cynthia Rudin
2019	J	`jnl`	Predictive Multiplicity in Classification. CoRR Charles T. Marx, Flávio du Pin Calmon, Berk Ustun
2019	A*	`conf`	Repairing without Retraining: Avoiding Disparate Impact with Counterfactual Distributions. ICML Hao Wang, Berk Ustun, Flávio P. Calmon
2019	J	`jnl`	Repairing without Retraining: Avoiding Disparate Impact with Counterfactual Distributions. CoRR Hao Wang, Berk Ustun, Flávio P. Calmon
2018	J	`jnl`	Actionable Recourse in Linear Classification. CoRR Berk Ustun, Alexander Spangher, Yang Liu
2018	B	`conf`	On the Direction of Discrimination: An Information-Theoretic Analysis of Disparate Impact in Machine Learning. ISIT Hao Wang, Berk Ustun, Flávio P. Calmon
2018	J	`jnl`	On the Direction of Discrimination: An Information-Theoretic Analysis of Disparate Impact in Machine Learning. CoRR Hao Wang, Berk Ustun, Flávio P. Calmon
2018	J	`jnl`	Optimized Scoring Systems: Toward Trust in Machine Learning for Healthcare and Criminal Justice. Interfaces Cynthia Rudin, Berk Ustun
2017	A*	`conf`	Optimized Risk Scores. KDD Berk Ustun, Cynthia Rudin
2017	—	`—`	Simple linear classifiers via discrete optimization: learning certifiably optimal scoring systems for decision-making and risk assessment. Berk Ustun
2016	J	`jnl`	Supersparse linear integer models for optimized medical scoring systems. Mach. Learn. Berk Ustun, Cynthia Rudin
2015	J	`jnl`	Importance Sampling in Stochastic Programming: A Markov Chain Monte Carlo Approach. INFORMS J. Comput. Panos Parpas, Berk Ustun, Mort Webster, Quang Kha Tran
2015	J	`jnl`	Supersparse Linear Integer Models for Optimized Medical Scoring Systems. CoRR Berk Ustun, Cynthia Rudin
2014	J	`jnl`	Methods and Models for Interpretable Linear Classification. CoRR Berk Ustun, Cynthia Rudin
2013	—	`conf`	Supersparse Linear Integer Models for Predictive Scoring Systems. AAAI (Late-Breaking Developments) Berk Ustun, Stefano Tracà, Cynthia Rudin