Towards Unbiased and Accurate Deferral to Multiple Experts

25 February 2021

Matthew Lease

Papers citing "Towards Unbiased and Accurate Deferral to Multiple Experts"

33 / 33 papers shown

Title
The Value of Information in Human-AI Decision-making Ziyang Guo Yifan Wu Jason D. Hartline Jessica Hullman FAtt 155 0 0 10 Feb 2025
To Ask or Not To Ask: Human-in-the-loop Contextual Bandits with Applications in Robot-Assisted Feeding Rohan Banerjee Rajat Kumar Jenamani Sidharth Vasudev Amal Nanavati Katherine Dimitropoulou Sarah Dean Tapomayukh Bhattacharjee 142 2 0 11 May 2024
Learning To Guide Human Decision Makers With Vision-Language Models Debodeep Banerjee Stefano Teso Burcu Sayin Andrea Passerini 50 1 0 25 Mar 2024
Learning Personalized Decision Support Policies Umang Bhatt Valerie Chen Katherine M. Collins Parameswaran Kamalaruban Emma Kallina Adrian Weller Ameet Talwalkar OffRL 153 11 0 13 Apr 2023
Minimax Group Fairness: Algorithms and Experiments Emily Diana Wesley Gill Michael Kearns K. Kenthapadi Aaron Roth FaML FedML 52 23 0 05 Nov 2020
Minimax Pareto Fairness: A Multi Objective Perspective Natalia Martínez Martín Bertrán Guillermo Sapiro FaML 59 191 0 03 Nov 2020
FrugalML: How to Use ML Prediction APIs More Accurately and Cheaply Lingjiao Chen Matei A. Zaharia James Zou 39 42 0 12 Jun 2020
Consistent Estimators for Learning to Defer to an Expert Hussein Mozannar David Sontag 49 201 0 02 Jun 2020
Learning to Complement Humans Bryan Wilder Eric Horvitz Ece Kamar 130 168 0 01 May 2020
Is the Most Accurate AI the Best Teammate? Optimizing AI for Teamwork Gagan Bansal Besmira Nushi Ece Kamar Eric Horvitz Daniel S. Weld 39 20 0 27 Apr 2020
Effect of Confidence and Explanation on Accuracy and Trust Calibration in AI-Assisted Decision Making Yunfeng Zhang Q. V. Liao Rachel K. E. Bellamy 73 674 0 07 Jan 2020
ORES: Lowering Barriers with Participatory Machine Learning in Wikipedia Aaron L Halfaker R. Geiger AI4TS KELM 114 20 0 11 Sep 2019
Regression Under Human Assistance A. De Nastaran Okati Paramita Koley Niloy Ganguly Manuel Gomez Rodriguez 128 62 0 06 Sep 2019
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 536 4,333 0 23 Aug 2019
Deep Gamblers: Learning to Abstain with Portfolio Theory Liu Ziyin Zhikang T. Wang Paul Pu Liang Ruslan Salakhutdinov Louis-Philippe Morency Masahito Ueda 68 112 0 29 Jun 2019
The Algorithmic Automation Problem: Prediction, Triage, and Human Effort M. Raghu Katy Blumer G. Corrado Jon M. Kleinberg Ziad Obermeyer S. Mullainathan 123 140 0 28 Mar 2019
Predicting the Type and Target of Offensive Posts in Social Media Marcos Zampieri S. Malmasi Preslav Nakov Sara Rosenthal N. Farra Ritesh Kumar 83 774 0 25 Feb 2019
Direct Uncertainty Prediction for Medical Second Opinions M. Raghu Katy Blumer Rory Sayres Ziad Obermeyer Robert D. Kleinberg S. Mullainathan Jon M. Kleinberg OOD UD 77 137 0 04 Jul 2018
Fairness Under Composition Cynthia Dwork Christina Ilvento FaML 81 126 0 15 Jun 2018
Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees L. E. Celis Lingxiao Huang Vijay Keswani Nisheeth K. Vishnoi FaML 182 308 0 15 Jun 2018
Delayed Impact of Fair Machine Learning Lydia T. Liu Sarah Dean Esther Rolf Max Simchowitz Moritz Hardt FaML 82 477 0 12 Mar 2018
A comparative study of fairness-enhancing interventions in machine learning Sorelle A. Friedler C. Scheidegger Suresh Venkatasubramanian Sonam Choudhary Evan P. Hamilton Derek Roth FaML 93 640 0 13 Feb 2018
How do Humans Understand Explanations from Machine Learning Systems? An Evaluation of the Human-Interpretability of Explanation Menaka Narayanan Emily Chen Jeffrey He Been Kim S. Gershman Finale Doshi-Velez FAtt XAI 94 242 0 02 Feb 2018
Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer David Madras T. Pitassi R. Zemel FaML 138 221 0 17 Nov 2017
On Fairness and Calibration Geoff Pleiss Manish Raghavan Felix Wu Jon M. Kleinberg Kilian Q. Weinberger FaML 168 876 0 06 Sep 2017
Fair Pipelines Amanda Bower Sarah Kitchen Laura Niss Martin Strauss Alexander Vargas Suresh Venkatasubramanian FaML 47 44 0 03 Jul 2017
Who Said What: Modeling Individual Labelers Improves Classification M. Guan Varun Gulshan Andrew M. Dai Geoffrey E. Hinton NoLa 40 226 0 26 Mar 2017
Automated Hate Speech Detection and the Problem of Offensive Language Thomas Davidson Dana Warmsley M. Macy Ingmar Weber 73 2,676 0 11 Mar 2017
Online Learning with Abstention Corinna Cortes Giulia DeSalvo Claudio Gentile M. Mohri Scott Yang 97 47 0 09 Mar 2017
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 295 2,109 0 24 Oct 2016
Equality of Opportunity in Supervised Learning Moritz Hardt Eric Price Nathan Srebro FaML 196 4,301 0 07 Oct 2016
Crowd Access Path Optimization: Diversity Matters Besmira Nushi Adish Singla Anja Gruenheid Erfan Zamanian Andreas Krause Donald Kossmann 40 18 0 08 Aug 2015
Cheaper and Better: Selecting Good Workers for Crowdsourcing Hongwei Li Qiang Liu 45 26 0 03 Feb 2015