v1v2 (latest)

Learning-to-defer for sequential medical decision-making under uncertainty

13 September 2021

Finale Doshi-Velez

Papers citing "Learning-to-defer for sequential medical decision-making under uncertainty"

23 / 23 papers shown

Title
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 163 2 0 11 May 2024
A Review of Off-Policy Evaluation in Reinforcement Learning Masatoshi Uehara C. Shi Nathan Kallus OffRL 92 76 0 13 Dec 2022
Incorporating Uncertainty in Learning to Defer Algorithms for Safe Computer-Aided Diagnosis Jessie Liu B. Gallego S. Barbieri 36 15 0 17 Aug 2021
Preferential Mixture-of-Experts: Interpretable Models that Rely on Human Expertise as much as Possible Melanie F. Pradier Javier Zazo S. Parbhoo R. Perlis Maurizio Zazzi Finale Doshi-Velez MoE 26 20 0 13 Jan 2021
Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty Umang Bhatt Javier Antorán Yunfeng Zhang Q. V. Liao P. Sattigeri ... L. Nachman R. Chunara Madhulika Srikumar Adrian Weller Alice Xiang 74 248 0 15 Nov 2020
Towards Safe Policy Improvement for Non-Stationary MDPs Yash Chandak Scott M. Jordan Georgios Theocharous Martha White Philip S. Thomas OffRL 95 34 0 23 Oct 2020
Expert-Supervised Reinforcement Learning for Offline Policy Learning and Evaluation W. AaronSonabend Junwei Lu Leo Anthony Celi Tianxi Cai Peter Szolovits OffRL 37 25 0 23 Jun 2020
Consistent Estimators for Learning to Defer to an Expert Hussein Mozannar David Sontag 54 204 0 02 Jun 2020
Optimizing for the Future in Non-Stationary MDPs Yash Chandak Georgios Theocharous Shiv Shankar Martha White Sridhar Mahadevan Philip S. Thomas OffRL 52 65 0 17 May 2020
Learning to Complement Humans Bryan Wilder Eric Horvitz Ece Kamar 165 168 0 01 May 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 83 677 0 07 Jan 2020
Off-Policy Evaluation in Partially Observable Environments Guy Tennenholtz Shie Mannor Uri Shalit OffRL 59 87 0 09 Sep 2019
Characterization of Overlap in Observational Studies Michael Oberst Fredrik D. Johansson Dennis L. Wei Tian Gao G. Brat David Sontag Kush R. Varshney CML 31 22 0 09 Jul 2019
Quality of Uncertainty Quantification for Bayesian Neural Network Inference Jiayu Yao Weiwei Pan S. Ghosh Finale Doshi-Velez UQCV BDL 181 113 0 24 Jun 2019
Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models Michael Oberst David Sontag CML OffRL 71 173 0 14 May 2019
Combining Parametric and Nonparametric Models for Off-Policy Evaluation Omer Gottesman Yao Liu Scott Sussex Emma Brunskill Finale Doshi-Velez OffRL 70 36 0 14 May 2019
The Algorithmic Automation Problem: Prediction, Triage, and Human Effort M. Raghu Katy Blumer G. Corrado Jon M. Kleinberg Ziad Obermeyer S. Mullainathan 156 140 0 28 Mar 2019
Expert-Augmented Machine Learning Efstathios D. Gennatas J. Friedman L. Ungar R. Pirracchio Eric Eaton ... A. Auerbach E. Delgado Mark van der Laan T. Solberg Gilmer Valdes 30 85 0 22 Mar 2019
Evaluating Reinforcement Learning Algorithms in Observational Health Settings Omer Gottesman Fredrik D. Johansson Joshua Meier Jack Dent Donghun Lee ... Matthieu Komorowski A. Faisal Leo Anthony Celi David Sontag Finale Doshi-Velez OOD OffRL 41 134 0 31 May 2018
Confounding-Robust Policy Improvement Nathan Kallus Angela Zhou CML OffRL 332 153 0 22 May 2018
Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer David Madras T. Pitassi R. Zemel FaML 163 221 0 17 Nov 2017
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 299 5,855 0 14 Jun 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 829 9,345 0 06 Jun 2015