Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer

17 November 2017

Papers citing "Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer"

50 / 50 papers shown

Title
Perils of Label Indeterminacy: A Case Study on Prediction of Neurological Recovery After Cardiac Arrest Jakob Schoeffer Maria De-Arteaga Jonathan Elmer 227 0 0 05 Apr 2025
Learning to Defer for Causal Discovery with Imperfect Experts Oscar Clivio Divyat Mahajan Perouz Taslakian Sara Magliacane Ioannis Mitliagkas Valentina Zantedeschi Alexandre Drouin CML 88 0 0 18 Feb 2025
The Value of Information in Human-AI Decision-making Ziyang Guo Yifan Wu Jason D. Hartline Jessica Hullman FAtt 64 0 0 10 Feb 2025
HR-Bandit: Human-AI Collaborated Linear Recourse Bandit Junyu Cao Ruijiang Gao Esmaeil Keyvanshokooh 45 1 0 18 Oct 2024
Unveiling AI's Blind Spots: An Oracle for In-Domain, Out-of-Domain, and Adversarial Errors Shuangpeng Han Mengmi Zhang 205 0 0 03 Oct 2024
Evaluating Human-AI Collaboration: A Review and Methodological Framework George Fragiadakis Christos Diou George Kousiouris Mara Nikolaidou 66 12 0 09 Jul 2024
Towards Integrating Personal Knowledge into Test-Time Predictions Isaac Lage S. Parbhoo Finale Doshi-Velez 27 1 0 12 Jun 2024
Building Socially-Equitable Public Models Yejia Liu Jianyi Yang Pengfei Li Tongxin Li Shaolei Ren OffRL 46 0 0 04 Jun 2024
A Causal Framework for Evaluating Deferring Systems Filippo Palomba Andrea Pugnana Jose M. Alvarez Salvatore Ruggieri CML 59 3 0 29 May 2024
Selective Annotation via Data Allocation: These Data Should Be Triaged to Experts for Annotation Rather Than the Model Chen Huang Yang Deng Wenqiang Lei Jiancheng Lv Ido Dagan 48 4 0 20 May 2024
Learning To Guide Human Decision Makers With Vision-Language Models Debodeep Banerjee Stefano Teso Burcu Sayin Andrea Passerini 40 1 0 25 Mar 2024
Specification Overfitting in Artificial Intelligence Benjamin Roth Pedro Henrique Luz de Araujo Yuxi Xia Saskia Kaltenbrunner Christoph Korab 58 0 0 13 Mar 2024
Investigating Gender Fairness in Machine Learning-driven Personalized Care for Chronic Pain Pratik Gajane Sean Newman Mykola Pechenizkiy John D. Piette FaML 28 0 0 29 Feb 2024
AI, Meet Human: Learning Paradigms for Hybrid Decision Making Systems Clara Punzi Roberto Pellungrini Mattia Setzu F. Giannotti D. Pedreschi 25 5 0 09 Feb 2024
A2C: A Modular Multi-stage Collaborative Decision Framework for Human-AI Teams Shahroz Tariq Mohan Baruwal Chhetri Surya Nepal Cécile Paris 45 6 0 25 Jan 2024
Theoretically Grounded Loss Functions and Algorithms for Score-Based Multi-Class Abstention Anqi Mao M. Mohri Yutao Zhong 34 22 0 23 Oct 2023
Confounding-Robust Policy Improvement with Human-AI Teams Ruijiang Gao Mingzhang Yin 37 3 0 13 Oct 2023
Learning to Abstain From Uninformative Data Yikai Zhang Songzhu Zheng M. Dalirrooyfard Pengxiang Wu Anderson Schneider Anant Raj Yuriy Nevmyvaka Chao Chen 26 2 0 25 Sep 2023
When Are Two Lists Better than One?: Benefits and Harms in Joint Decision-making Kate Donahue Sreenivas Gollapudi Kostas Kollias 37 3 0 22 Aug 2023
Co-creating a globally interpretable model with human input Rahul Nair 9 0 0 23 Jun 2023
In Search of Verifiability: Explanations Rarely Enable Complementary Performance in AI-Advised Decision Making Raymond Fok Daniel S. Weld 34 61 0 12 May 2023
Data-Driven Subgroup Identification for Linear Regression Zachary Izzo Ruishan Liu James Zou OOD 23 4 0 29 Apr 2023
Learning Personalized Decision Support Policies Umang Bhatt Valerie Chen Katherine M. Collins Parameswaran Kamalaruban Emma Kallina Adrian Weller Ameet Talwalkar OffRL 58 10 0 13 Apr 2023
Who Should Predict? Exact Algorithms For Learning to Defer to Humans Hussein Mozannar Hunter Lang Dennis L. Wei P. Sattigeri Subhro Das David Sontag 32 43 0 15 Jan 2023
Counterfactuals for the Future Lucius E.J. Bynum Joshua R. Loftus Julia Stoyanovich 33 10 0 07 Dec 2022
FEAMOE: Fair, Explainable and Adaptive Mixture of Experts Shubham Sharma Jette Henderson Joydeep Ghosh FedML MoE 28 5 0 10 Oct 2022
Learning When to Advise Human Decision Makers Gali Noti Yiling Chen 50 15 0 27 Sep 2022
Sample Efficient Learning of Predictors that Complement Humans Mohammad-Amin Charusaie Hussein Mozannar David Sontag Samira Samadi 46 33 0 19 Jul 2022
Forming Effective Human-AI Teams: Building Machine Learning Models that Complement the Capabilities of Multiple Experts Patrick Hemmer Sebastian Schellhammer Michael Vossing Johannes Jakubik G. Satzger 42 37 0 16 Jun 2022
CARD: Classification and Regression Diffusion Models Xizewen Han Huangjie Zheng Mingyuan Zhou DiffM 54 109 0 15 Jun 2022
Who Goes First? Influences of Human-AI Workflow on Decision Making in Clinical Imaging Riccardo Fogliato Shreya Chappidi M. Lungren Michael Fitzke Mark Parkinson Diane U Wilson Paul Fisher Eric Horvitz K. Inkpen Besmira Nushi 24 70 0 19 May 2022
Trucks Don't Mean Trump: Diagnosing Human Error in Image Analysis J.D. Zamfirescu-Pereira Jerry Chen Emily Wen Allison Koenecke N. Garg Emma Pierson 24 5 0 15 May 2022
Affective Medical Estimation and Decision Making via Visualized Learning and Deep Learning M. Eslami Solale Tabarestani Ehsan Adeli G. Elwyn T. Elze Mengyu Wang Nazlee Zebardast Nassir Navab M. Adjouadi 16 0 0 09 May 2022
On the Utility of Prediction Sets in Human-AI Teams Varun Babbar Umang Bhatt Adrian Weller 28 31 0 03 May 2022
Doubting AI Predictions: Influence-Driven Second Opinion Recommendation Maria De-Arteaga Alexandra Chouldechova Artur Dubrawski 33 4 0 29 Apr 2022
Calibrated Learning to Defer with One-vs-All Classifiers Rajeev Verma Eric Nalisnick 26 43 0 08 Feb 2022
Improving Learning-to-Defer Algorithms Through Fine-Tuning Naveen Raman Michael Yee 21 8 0 18 Dec 2021
Teaching Humans When To Defer to a Classifier via Exemplars Hussein Mozannar Arvindmani Satyanarayan David Sontag 41 43 0 22 Nov 2021
Combining Human Predictions with Model Probabilities via Confusion Matrices and Calibration Gavin Kerrigan Padhraic Smyth M. Steyvers 30 48 0 29 Sep 2021
Incorporating Uncertainty in Learning to Defer Algorithms for Safe Computer-Aided Diagnosis Jessie Liu B. Gallego S. Barbieri 27 14 0 17 Aug 2021
Disaggregated Interventions to Reduce Inequality Lucius E.J. Bynum Joshua R. Loftus Julia Stoyanovich 42 13 0 01 Jul 2021
Human-AI Collaboration with Bandit Feedback Ruijiang Gao M. Saar-Tsechansky Maria De-Arteaga Ligong Han Min Kyung Lee Matthew Lease 54 49 0 22 May 2021
CheXbreak: Misclassification Identification for Deep Learning Models Interpreting Chest X-rays E. Chen Andy Kim R. Krishnan J. Long A. Ng Pranav Rajpurkar 26 2 0 18 Mar 2021
Differentiable Learning Under Triage Nastaran Okati A. De Manuel Gomez Rodriguez 38 63 0 16 Mar 2021
Why have a Unified Predictive Uncertainty? Disentangling it using Deep Split Ensembles U. Sarawgi W. Zulfikar Rishab Khincha Pattie Maes PER UQCV BDL UD 23 7 0 25 Sep 2020
Unifying Model Explainability and Robustness via Machine-Checkable Concepts Vedant Nanda Till Speicher John P. Dickerson Krishna P. Gummadi Muhammad Bilal Zafar AAML 14 4 0 01 Jul 2020
Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance Gagan Bansal Tongshuang Wu Joyce Zhou Raymond Fok Besmira Nushi Ece Kamar Marco Tulio Ribeiro Daniel S. Weld 42 584 0 26 Jun 2020
Review of Mathematical frameworks for Fairness in Machine Learning E. del Barrio Paula Gordaliza Jean-Michel Loubes FaML FedML 15 39 0 26 May 2020
Learning Representations by Humans, for Humans Sophie Hilgard Nir Rosenfeld M. Banaji Jack Cao David C. Parkes OCL HAI AI4CE 34 29 0 29 May 2019
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 207 2,092 0 24 Oct 2016