Berk Ustun

发表

Interpretable classification models for recidivism prediction

Cynthia Rudin, Berk Ustun, Jiaming Zeng, 2015, 1503.07810.

When Personalization Harms: Reconsidering the Use of Group Attributes in Prediction

V. Suriyakumar, M. Ghassemi, Berk Ustun, 2022, ArXiv.

Predictive Multiplicity in Probabilistic Classification

D. Parkes, Berk Ustun, J. Watson-Daniels, 2022, AAAI Conference on Artificial Intelligence.

Rank List Sensitivity of Recommender Systems to Interaction Perturbations

Julian McAuley, Berk Ustun, Srijan Kumar, 2022, CIKM.

Methods and Models for Interpretable Linear Classification pdf

Cynthia Rudin, Berk Ustun, C. Rudin, 2014, ArXiv.

Participatory Systems for Personalized Prediction

K. Heller, Berk Ustun, Chirag Nagpal, 2023, ArXiv.

Learning Optimized Risk Scores

Cynthia Rudin, Berk Ustun, C. Rudin, 2016, J. Mach. Learn. Res..

Supersparse linear integer models for optimized medical scoring systems

Cynthia Rudin, Berk Ustun, C. Rudin, 2015, Machine Learning.

Supersparse Linear Integer Models for Interpretable Classification

Cynthia Rudin, Berk Ustun, Stefano Traca, 2013, 1306.6677.

Supersparse Linear Integer Models for Predictive Scoring Systems

Cynthia Rudin, Berk Ustun, Stefano Tracà, 2013, AAAI.

Optimized Risk Scores

Cynthia Rudin, Berk Ustun, C. Rudin, 2017, KDD.

When Personalization Harms: Reconsidering the Use of Group Attributes in Prediction

V. Suriyakumar, M. Ghassemi, Berk Ustun, 2022, ArXiv.

Optimized Scoring Systems: Toward Trust in Machine Learning for Healthcare and Criminal Justice

Cynthia Rudin, Berk Ustun, C. Rudin, 2018, Interfaces.

Actionable Recourse in Linear Classification

Yang Liu, Berk Ustun, Alexander Spangher, 2018, FAT.

Predictive Multiplicity in Classification

F. Calmon, Berk Ustun, Charles T. Marx, 2019, ICML.

Developing an optimal short‐form of the PTSD Checklist for DSM‐5 (PCL‐5)

Murray B Stein, Kelly L Zuromski, Berk Ustun, 2019, Depression and anxiety.

The World Health Organization Adult Attention-Deficit/Hyperactivity Disorder Self-Report Screening Scale for DSM-5

Cynthia Rudin, Ronald C. Kessler, Stephen V. Faraone, 2017, JAMA psychiatry.

Clinical Prediction Models for Sleep Apnea: The Importance of Medical History over Symptoms.

C. Rudin, Berk Ustun, M. Westover, 2016, Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine.

Fairness without Harm: Decoupled Classifiers with Preference Guarantees

David C. Parkes, Berk Ustun, Yang Liu, 2019, ICML.

Learning Optimal Predictive Checklists pdf

Berk Ustun, Marzyeh Ghassemi, Haoran Zhang, 2021, NeurIPS.

Development and Validation of a Model to Predict Posttraumatic Stress Disorder and Major Depression After a Motor Vehicle Collision.

Christopher W. Jones, S. Rauch, K. Ressler, 2021, JAMA psychiatry.

Repairing without Retraining: Avoiding Disparate Impact with Counterfactual Distributions

Berk Ustun, Hao Wang, Flávio P. Calmon, 2019, ICML.

Association of an Electroencephalography-Based Risk Score With Seizure Probability in Hospitalized Patients

Hiba A. Haider, C. Rudin, Berk Ustun, 2017, JAMA neurology.

When Personalization Harms Performance: Reconsidering the Use of Group Attributes in Prediction

Vinith M. Suriyakumar, V. Suriyakumar, M. Ghassemi, 2022, ICML.

Optimized short-forms of the Cognitive Distortions Questionnaire.

R. Kessler, J. Gross, Berk Ustun, 2022, Journal of anxiety disorders.

Simple linear classifiers via discrete optimization: learning certifiably optimal scoring systems for decision-making and risk assessment

Berk Ustun, Berk Ustun, 2017 .

On the Direction of Discrimination: An Information-Theoretic Analysis of Disparate Impact in Machine Learning

Hao Wang, Berk Ustun, Flávio du Pin Calmon, 2018, 2018 IEEE International Symposium on Information Theory (ISIT).

Algorithmic Censoring in Dynamic Learning Systems

Margaret E. Roberts, Berk Ustun, Jennifer Chien, 2023, EAAMO.

Prediction without Preclusion: Recourse Verification with Reachable Sets

Berk Ustun, Tsui-Wei Weng, B. Kulynych, 2023, ArXiv.

Importance Sampling in Stochastic Programming: A Markov Chain Monte Carlo Approach

Berk Ustun, Panos Parpas, Mort Webster, 2015, INFORMS J. Comput..

The Markov chain Monte Carlo approach to importance sampling in stochastic programming

Berk Ustun, Berk Ustun, 2012 .

Predictive Multiplicity in Probabilistic Classification

D. Parkes, Berk Ustun, J. Watson-Daniels, 2022, AAAI.

Algorithmic Censoring in Dynamic Learning Systems

Margaret E. Roberts, Berk Ustun, Jennifer Chien, 2023, EAAMO.

FINEST: Stabilizing Recommendations by Rank-Preserving Fine-Tuning

Berk Ustun, Sejoon Oh, Julian McAuley, 2024, ArXiv.

Participatory Personalization in Classification

K. Heller, Berk Ustun, Chirag Nagpal, 2023, NeurIPS.

Predictive Churn with the Set of Good Models

Berk Ustun, J. Watson-Daniels, Alexander D'Amour, 2024, 2402.07745.