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Berk Ustun
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2020 – today
- 2024
- [c18]Jayanth Yetukuri, Ian Hardy, Yevgeniy Vorobeychik, Berk Ustun, Yang Liu:
Providing Fair Recourse over Plausible Groups. AAAI 2024: 21753-21760 - [c17]Talia B. Gillis
, Vitaly Meursault
Operationalizing the Search for Less Discriminatory Alternatives in Fair Lending. FAccT 2024: 377-387 - [c16]Hailey Joren, Charles T. Marx, Berk Ustun
Classification with Conceptual Safeguards. ICLR 2024 - [c15]Avni Kothari, Bogdan Kulynych, Tsui-Wei Weng, Berk Ustun
Prediction without Preclusion: Recourse Verification with Reachable Sets. ICLR 2024 - [i16]Sejoon Oh, Berk Ustun, Julian J. McAuley, Srijan Kumar:
FINEST: Stabilizing Recommendations by Rank-Preserving Fine-Tuning. CoRR abs/2402.03481 (2024) - [i15]Sujay Nagaraj, Walter Gerych, Sana Tonekaboni, Anna Goldenberg, Berk Ustun, Thomas Hartvigsen:
Learning from Time Series under Temporal Label Noise. CoRR abs/2402.04398 (2024) - [i14]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 abs/2402.07745 (2024) - [i13]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
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium. CoRR abs/2403.01628 (2024) - 2023
- [c14]Jamelle Watson-Daniels, David C. Parkes, Berk Ustun
Predictive Multiplicity in Probabilistic Classification. AAAI 2023: 10306-10314 - [c13]Jennifer Chien
Algorithmic Censoring in Dynamic Learning Systems. EAAMO 2023: 26:1-26:20 - [c12]Vinith Menon Suriyakumar, Marzyeh Ghassemi, Berk Ustun
When Personalization Harms Performance: Reconsidering the Use of Group Attributes in Prediction. ICML 2023: 33209-33228 - [c11]Hailey Joren, Chirag Nagpal, Katherine A. Heller, Berk Ustun:
Participatory Personalization in Classification. NeurIPS 2023 - [i12]Hailey James, Chirag Nagpal, Katherine A. Heller, Berk Ustun:
Participatory Systems for Personalized Prediction. CoRR abs/2302.03874 (2023) - [i11]Jennifer Chien, Margaret E. Roberts, Berk Ustun:
Algorithmic Censoring in Dynamic Learning Systems. CoRR abs/2305.09035 (2023) - [i10]Avni Kothari, Bogdan Kulynych, Tsui-Wei Weng, Berk Ustun:
Prediction without Preclusion: Recourse Verification with Reachable Sets. CoRR abs/2308.12820 (2023) - 2022
- [c10]Sejoon Oh
Rank List Sensitivity of Recommender Systems to Interaction Perturbations. CIKM 2022: 1584-1594 - [c9]Lucas Monteiro Paes, Carol Xuan Long, Berk Ustun, Flávio P. Calmon:
On the Epistemic Limits of Personalized Prediction. NeurIPS 2022 - [i9]Jamelle Watson-Daniels, David C. Parkes, Berk Ustun:
Predictive Multiplicity in Probabilistic Classification. CoRR abs/2206.01131 (2022) - [i8]Vinith M. Suriyakumar, Marzyeh Ghassemi, Berk Ustun:
When Personalization Harms: Reconsidering the Use of Group Attributes in Prediction. CoRR abs/2206.02058 (2022) - 2021
- [c8]Haoran Zhang, Quaid Morris, Berk Ustun, Marzyeh Ghassemi:
Learning Optimal Predictive Checklists. NeurIPS 2021: 1215-1229 - [i7]Haoran Zhang, Quaid Morris, Berk Ustun, Marzyeh Ghassemi:
Learning Optimal Predictive Checklists. CoRR abs/2112.01020 (2021) - 2020
- [c7]Charles T. Marx, Flávio P. Calmon, Berk Ustun:
Predictive Multiplicity in Classification. ICML 2020: 6765-6774
2010 – 2019
- 2019
- [j4]Berk Ustun
Learning Optimized Risk Scores. J. Mach. Learn. Res. 20: 150:1-150:75 (2019) - [c6]Berk Ustun
Actionable Recourse in Linear Classification. FAT 2019: 10-19 - [c5]Berk Ustun, Yang Liu, David C. Parkes:
Fairness without Harm: Decoupled Classifiers with Preference Guarantees. ICML 2019: 6373-6382 - [c4]Hao Wang, Berk Ustun, Flávio P. Calmon:
Repairing without Retraining: Avoiding Disparate Impact with Counterfactual Distributions. ICML 2019: 6618-6627 - [i6]Hao Wang, Berk Ustun, Flávio P. Calmon:
Repairing without Retraining: Avoiding Disparate Impact with Counterfactual Distributions. CoRR abs/1901.10501 (2019) - [i5]Charles T. Marx, Flávio du Pin Calmon, Berk Ustun:
Predictive Multiplicity in Classification. CoRR abs/1909.06677 (2019) - 2018
- [j3]Cynthia Rudin
Optimized Scoring Systems: Toward Trust in Machine Learning for Healthcare and Criminal Justice. Interfaces 48(5): 449-466 (2018) - [c3]Hao Wang, Berk Ustun, Flávio P. Calmon:
On the Direction of Discrimination: An Information-Theoretic Analysis of Disparate Impact in Machine Learning. ISIT 2018: 126-130 - [i4]Hao Wang, Berk Ustun, Flávio P. Calmon:
On the Direction of Discrimination: An Information-Theoretic Analysis of Disparate Impact in Machine Learning. CoRR abs/1801.05398 (2018) - [i3]Berk Ustun, Alexander Spangher, Yang Liu:
Actionable Recourse in Linear Classification. CoRR abs/1809.06514 (2018) - 2017
- [b1]Berk Ustun:
Simple linear classifiers via discrete optimization: learning certifiably optimal scoring systems for decision-making and risk assessment. Massachusetts Institute of Technology, Cambridge, USA, 2017 - [c2]Berk Ustun
Optimized Risk Scores. KDD 2017: 1125-1134 - 2016
- [j2]Berk Ustun
Supersparse linear integer models for optimized medical scoring systems. Mach. Learn. 102(3): 349-391 (2016) - 2015
- [j1]Panos Parpas
Importance Sampling in Stochastic Programming: A Markov Chain Monte Carlo Approach. INFORMS J. Comput. 27(2): 358-377 (2015) - [i2]Berk Ustun, Cynthia Rudin:
Supersparse Linear Integer Models for Optimized Medical Scoring Systems. CoRR abs/1502.04269 (2015) - 2014
- [i1]Berk Ustun, Cynthia Rudin:
Methods and Models for Interpretable Linear Classification. CoRR abs/1405.4047 (2014) - 2013
- [c1]Berk Ustun, Stefano Tracà, Cynthia Rudin:
Supersparse Linear Integer Models for Predictive Scoring Systems. AAAI (Late-Breaking Developments) 2013
Coauthor Index
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last updated on 2024-10-07 21:24 CEST by the dblp team
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