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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 / 139 papers shown

Title
How Far Can Fairness Constraints Help Recover From Biased Data? Mohit Sharma Amit Deshpande FaML 120 2 0 16 Dec 2023
Bayesian Online Learning for Consensus Prediction Sam Showalter Alex Boyd Padhraic Smyth M. Steyvers 56 2 0 12 Dec 2023
Learning to Complement with Multiple Humans Zheng Zhang Cuong C. Nguyen Kevin Wells Thanh-Toan Do Gustavo Carneiro 75 0 0 22 Nov 2023
In Defense of Softmax Parametrization for Calibrated and Consistent Learning to Defer Yuzhou Cao Hussein Mozannar Lei Feng Hongxin Wei Bo An 108 19 0 02 Nov 2023
Effective Human-AI Teams via Learned Natural Language Rules and Onboarding Hussein Mozannar Jimin J Lee Dennis L. Wei P. Sattigeri Subhro Das David Sontag 131 13 0 02 Nov 2023
Predictor-Rejector Multi-Class Abstention: Theoretical Analysis and Algorithms Anqi Mao M. Mohri Yutao Zhong 88 27 0 23 Oct 2023
Theoretically Grounded Loss Functions and Algorithms for Score-Based Multi-Class Abstention Anqi Mao M. Mohri Yutao Zhong 50 24 0 23 Oct 2023
Confounding-Robust Policy Improvement with Human-AI Teams Ruijiang Gao Mingzhang Yin 444 4 0 13 Oct 2023
Fair Classifiers that Abstain without Harm Tongxin Yin Jean-François Ton Ruocheng Guo Yuanshun Yao Mingyan Liu Yang Liu 60 5 0 09 Oct 2023
Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and Tools Maximilian Schambach Rakshit Naidu Rayid Ghani Kit T. Rodolfa Daniel E. Ho Hoda Heidari FaML 87 17 0 29 Sep 2023
Learning to Abstain From Uninformative Data Yikai Zhang Songzhu Zheng M. Dalirrooyfard Pengxiang Wu Anderson Schneider Anant Raj Yuriy Nevmyvaka Chao Chen 48 2 0 25 Sep 2023
Know What Not To Know: Users' Perception of Abstaining Classifiers A. Papenmeier Daniel Hienert Yvonne Kammerer C. Seifert Dagmar Kern HAI 93 1 0 11 Sep 2023
Muffin: A Framework Toward Multi-Dimension AI Fairness by Uniting Off-the-Shelf Models Yi Sheng Junhuan Yang Lei Yang Yiyu Shi Jiaxi Hu Weiwen Jiang 66 9 0 26 Aug 2023
When Are Two Lists Better than One?: Benefits and Harms in Joint Decision-making Kate Donahue Sreenivas Gollapudi Kostas Kollias 73 4 0 22 Aug 2023
Learning to Guide Human Experts via Personalized Large Language Models Debodeep Banerjee Stefano Teso Andrea Passerini LLMAG 45 0 0 11 Aug 2023
When Does Confidence-Based Cascade Deferral Suffice? Wittawat Jitkrittum Neha Gupta A. Menon Harikrishna Narasimhan A. S. Rawat Surinder Kumar 53 23 0 06 Jul 2023
Co-creating a globally interpretable model with human input Rahul Nair 38 0 0 23 Jun 2023
Towards Regulatable AI Systems: Technical Gaps and Policy Opportunities Xudong Shen H. Brown Jiashu Tao Martin Strobel Yao Tong Akshay Narayan Harold Soh Finale Doshi-Velez 98 3 0 22 Jun 2023
When to Show a Suggestion? Integrating Human Feedback in AI-Assisted Programming Hussein Mozannar Gagan Bansal Adam Fourney Eric Horvitz 107 28 0 08 Jun 2023
Auditing for Human Expertise Rohan Alur Loren Laine Darrick K. Li Manish Raghavan Devavrat Shah Dennis L. Shung 57 8 0 02 Jun 2023
Counterfactually Comparing Abstaining Classifiers Yo Joong Choe Aditya Gangrade Aaditya Ramdas 62 1 0 17 May 2023
In Search of Verifiability: Explanations Rarely Enable Complementary Performance in AI-Advised Decision Making Raymond Fok Daniel S. Weld 104 67 0 12 May 2023
Data-Driven Subgroup Identification for Linear Regression Zachary Izzo Ruishan Liu James Zou OOD 72 4 0 29 Apr 2023
Learning to Defer with Limited Expert Predictions Patrick Hemmer Lukas Thede Michael Vossing Johannes Jakubik Niklas Kühl 45 15 0 14 Apr 2023
Learning Personalized Decision Support Policies Umang Bhatt Valerie Chen Katherine M. Collins Parameswaran Kamalaruban Emma Kallina Adrian Weller Ameet Talwalkar OffRL 220 11 0 13 Apr 2023
Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation Angie Zhang Olympia Walker Kaci Nguyen Jiajun Dai Anqing Chen Min Kyung Lee 73 50 0 22 Feb 2023
Ground(less) Truth: A Causal Framework for Proxy Labels in Human-Algorithm Decision-Making Luke M. Guerdan Amanda Coston Zhiwei Steven Wu Kenneth Holstein CML 82 30 0 13 Feb 2023
Learning Complementary Policies for Human-AI Teams Ruijiang Gao M. Saar-Tsechansky Maria De-Arteaga Ligong Han Wei-Ju Sun Min Kyung Lee Matthew Lease 192 9 0 06 Feb 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 100 51 0 15 Jan 2023
Who Should I Trust: AI or Myself? Leveraging Human and AI Correctness Likelihood to Promote Appropriate Trust in AI-Assisted Decision-Making Shuai Ma Ying Lei Xinru Wang Chengbo Zheng Chuhan Shi Ming Yin Xiaojuan Ma 81 105 0 14 Jan 2023
Counterfactuals for the Future Lucius E.J. Bynum Joshua R. Loftus Julia Stoyanovich 60 10 0 07 Dec 2022
Algorithmic Decision-Making Safeguarded by Human Knowledge Ningyuan Chen Mingya Hu Wenhao Li 59 5 0 20 Nov 2022
Learning to Defer to Multiple Experts: Consistent Surrogate Losses, Confidence Calibration, and Conformal Ensembles Rajeev Verma Daniel Barrejón Eric Nalisnick UQCV 62 35 0 30 Oct 2022
Learning to Advise Humans in High-Stakes Settings Nicholas Wolczynski M. Saar-Tsechansky Tong Wang 53 0 0 23 Oct 2022
FEAMOE: Fair, Explainable and Adaptive Mixture of Experts Shubham Sharma Jette Henderson Joydeep Ghosh FedML MoE 48 5 0 10 Oct 2022
Learning When to Advise Human Decision Makers Gali Noti Yiling Chen 104 16 0 27 Sep 2022
Taking Advice from (Dis)Similar Machines: The Impact of Human-Machine Similarity on Machine-Assisted Decision-Making Nina Grgic-Hlaca C. Castelluccia Krishna P. Gummadi HAI 65 13 0 08 Sep 2022
Toward Supporting Perceptual Complementarity in Human-AI Collaboration via Reflection on Unobservables Kenneth Holstein Maria De-Arteaga Lakshmi Tumati Yanghuidi Cheng 190 27 0 28 Jul 2022
Sample Efficient Learning of Predictors that Complement Humans Mohammad-Amin Charusaie Hussein Mozannar David Sontag Samira Samadi 73 34 0 19 Jul 2022
Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey Max Hort Zhenpeng Chen Jie M. Zhang Mark Harman Federica Sarro FaML AI4CE 107 177 0 14 Jul 2022
Bottlenecks CLUB: Unifying Information-Theoretic Trade-offs Among Complexity, Leakage, and Utility Behrooz Razeghi Flavio du Pin Calmon Deniz Gunduz Svyatoslav Voloshynovskiy 58 16 0 11 Jul 2022
An Embedding Framework for the Design and Analysis of Consistent Polyhedral Surrogates Jessie Finocchiaro Rafael Frongillo Bo Waggoner 103 14 0 29 Jun 2022
Human-AI Collaboration in Decision-Making: Beyond Learning to Defer Diogo Leitao Pedro Saleiro Mário A. T. Figueiredo P. Bizarro 74 21 0 27 Jun 2022
Three Applications of Conformal Prediction for Rating Breast Density in Mammography Charles Lu Ken Chang Praveer Singh Jayashree Kalpathy-Cramer OOD AI4CE 82 8 0 23 Jun 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 72 39 0 16 Jun 2022
CARD: Classification and Regression Diffusion Models Xizewen Han Huangjie Zheng Mingyuan Zhou DiffM 108 116 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 89 72 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 58 6 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 42 0 0 09 May 2022
On the Utility of Prediction Sets in Human-AI Teams Varun Babbar Umang Bhatt Adrian Weller 75 33 0 03 May 2022