Machine Learning with a Reject Option: A survey

23 July 2021

Papers citing "Machine Learning with a Reject Option: A survey"

50 / 64 papers shown

Title
A Connection Between Learning to Reject and Bhattacharyya Divergences Alexander Soen 53 0 0 08 May 2025
Regretful Decisions under Label Noise Sujay Nagaraj Yang Liu Flavio du Pin Calmon Berk Ustun NoLa 58 1 0 12 Apr 2025
Towards Reliable Time Series Forecasting under Future Uncertainty: Ambiguity and Novelty Rejection Mechanisms Ninghui Feng Songning Lai Xin Zhou Jiayu Yang Kunlong Feng ... Zhangyi Hu Yutao Yue Yuxuan Liang Boyu Wang Hang Zhao AI4TS 52 0 0 25 Mar 2025
Interpretable and Fair Mechanisms for Abstaining Classifiers Daphne Lenders Andrea Pugnana Roberto Pellungrini Toon Calders D. Pedreschi F. Giannotti FaML 89 1 0 24 Mar 2025
Exploring the Potential of Bilevel Optimization for Calibrating Neural Networks Gabriele Sanguin Arjun Pakrashi Marco Viola Francesco Rinaldi 56 0 0 17 Mar 2025
Conceptualizing Uncertainty Isaac Roberts Alexander Schulz Sarah Schroeder Fabian Hinder Barbara Hammer UD 77 0 0 05 Mar 2025
Safety Monitoring of Machine Learning Perception Functions: a Survey Raul Sena Ferreira Joris Guérin Kevin Delmas Jérémie Guiochet H. Waeselynck 67 0 0 09 Dec 2024
Classification with Conceptual Safeguards Hailey Joren Charles Marx Berk Ustun 37 2 0 07 Nov 2024
On the Robustness of Adversarial Training Against Uncertainty Attacks Emanuele Ledda Giovanni Scodeller Daniele Angioni Giorgio Piras Antonio Emanuele Cinà Giorgio Fumera Battista Biggio Fabio Roli AAML 30 1 0 29 Oct 2024
Conjunction Subspaces Test for Conformal and Selective Classification Zengyou He Zerun Li Junjie Dong Xinying Liu Mudi Jiang Lianyu Hu 18 0 0 16 Oct 2024
FairlyUncertain: A Comprehensive Benchmark of Uncertainty in Algorithmic Fairness Lucas Rosenblatt R. T. Witter FaML 20 0 0 02 Oct 2024
Learning To Help: Training Models to Assist Legacy Devices Yu Wu Anand Sarwate 27 1 0 24 Sep 2024
Abstaining Machine Learning -- Philosophical Considerations Daniela Schuster 23 0 0 01 Sep 2024
Finding Patterns in Ambiguity: Interpretable Stress Testing in the Decision~Boundary Ines Gomes Luís F. Teixeira Jan N. van Rijn Carlos Soares André Restivo Luís Cunha Moisés Santos FAtt 27 1 0 12 Aug 2024
A3Rank: Augmentation Alignment Analysis for Prioritizing Overconfident Failing Samples for Deep Learning Models Zhengyuan Wei Haipeng Wang Qili Zhou William Chan 34 0 0 19 Jul 2024
LAB-Bench: Measuring Capabilities of Language Models for Biology Research Jon M. Laurent Joseph D. Janizek Michael Ruzo Michaela M. Hinks M. Hammerling Siddharth Narayanan Manvitha Ponnapati Andrew D. White Samuel G. Rodriques ELM 25 36 0 14 Jul 2024
Integrating White and Black Box Techniques for Interpretable Machine Learning E. Vernon Naoki Masuyama Yusuke Nojima 25 2 0 12 Jul 2024
Stacked Confusion Reject Plots (SCORE) Stephan Hasler Lydia Fischer 21 0 0 25 Jun 2024
Towards Robust Training Datasets for Machine Learning with Ontologies: A Case Study for Emergency Road Vehicle Detection Lynn Vonderhaar Timothy Elvira T. Procko Omar Ochoa 26 0 0 21 Jun 2024
EMOE: Expansive Matching of Experts for Robust Uncertainty Based Rejection Yunni Qu James Wellnitz Alexander Tropsha Junier Oliva 36 0 0 03 Jun 2024
Policy Trees for Prediction: Interpretable and Adaptive Model Selection for Machine Learning Dimitris Bertsimas Matthew Peroni OffRL 25 0 0 30 May 2024
Rejection via Learning Density Ratios Alexander Soen Hisham Husain Philip Schulz Vu-Linh Nguyen 47 2 0 29 May 2024
A Causal Framework for Evaluating Deferring Systems Filippo Palomba Andrea Pugnana Jose M. Alvarez Salvatore Ruggieri CML 48 1 0 29 May 2024
Sample Selection Bias in Machine Learning for Healthcare V. Chauhan Lei A. Clifton Achille Salaün Huiqi Yvonne Lu Kim Branson Patrick Schwab Gaurav Nigam David A. Clifton 41 1 0 13 May 2024
Machine Learning Robustness: A Primer Houssem Ben Braiek Foutse Khomh AAML OOD 34 5 0 01 Apr 2024
Bandits with Abstention under Expert Advice Stephen Pasteris Alberto Rumi Maximilian Thiessen Shota Saito Atsushi Miyauchi Fabio Vitale Mark Herbster 21 1 0 22 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 31 6 0 25 Jan 2024
Towards Context-Aware Domain Generalization: Understanding the Benefits and Limits of Marginal Transfer Learning Jens Müller Lars Kühmichel Martin Rohbeck Stefan T. Radev Ullrich Kothe OOD 37 0 0 15 Dec 2023
Model Agnostic Explainable Selective Regression via Uncertainty Estimation Andrea Pugnana Carlos Mougan Dan Saattrup Nielsen 33 0 0 15 Nov 2023
Online Decision Mediation Daniel Jarrett Alihan Huyuk M. Schaar 33 2 0 28 Oct 2023
Precision and Recall Reject Curves for Classification Lydia Fischer Patricia Wollstadt 9 1 0 16 Aug 2023
Robust Ordinal Regression for Subsets Comparisons with Interactions Hugo Gilbert Mohamed Ouaguenouni Meltem Öztürk Olivier Spanjaard 14 0 0 07 Aug 2023
Empirical Optimal Risk to Quantify Model Trustworthiness for Failure Detection Shuang Ao Stefan Rueger Advaith Siddharthan 25 2 0 06 Aug 2023
Two Sides of Miscalibration: Identifying Over and Under-Confidence Prediction for Network Calibration Shuang Ao Stefan Rueger Advaith Siddharthan UQCV 13 8 0 06 Aug 2023
How do you feel? Measuring User-Perceived Value for Rejecting Machine Decisions in Hate Speech Detection Philippe Lammerts Philip Lippmann Yen-Chia Hsu Fabio Casati Jie Yang 23 0 0 21 Jul 2023
When Does Confidence-Based Cascade Deferral Suffice? Wittawat Jitkrittum Neha Gupta A. Menon Harikrishna Narasimhan A. S. Rawat Surinder Kumar 17 18 0 06 Jul 2023
Explaining Predictive Uncertainty with Information Theoretic Shapley Values David S. Watson Joshua O'Hara Niek Tax Richard Mudd Ido Guy TDI FAtt 26 21 0 09 Jun 2023
U-PASS: an Uncertainty-guided deep learning Pipeline for Automated Sleep Staging E. Heremans Nabeel Seedat B. Buyse D. Testelmans M. Schaar Marina De Vos 24 5 0 07 Jun 2023
How to Fix a Broken Confidence Estimator: Evaluating Post-hoc Methods for Selective Classification with Deep Neural Networks L. F. P. Cattelan Danilo Silva UQCV 27 5 0 24 May 2023
Unsupervised Anomaly Detection with Rejection Lorenzo Perini Jesse Davis 21 7 0 22 May 2023
Counterfactually Comparing Abstaining Classifiers Yo Joong Choe Aditya Gangrade Aaditya Ramdas 14 1 0 17 May 2023
Survey on Leveraging Uncertainty Estimation Towards Trustworthy Deep Neural Networks: The Case of Reject Option and Post-training Processing M. Hasan Moloud Abdar Abbas Khosravi U. Aickelin Pietro Lio' Ibrahim Hossain Ashikur Rahman Saeid Nahavandi 30 4 0 11 Apr 2023
Finding Competence Regions in Domain Generalization Jens Müller Stefan T. Radev R. Schmier Felix Dräxler Carsten Rother Ullrich Kothe 16 4 0 17 Mar 2023
A Review of and Roadmap for Data Science and Machine Learning for the Neuropsychiatric Phenotype of Autism Peter Washington Dennis Paul Wall 24 40 0 07 Mar 2023
Fast Online Value-Maximizing Prediction Sets with Conformal Cost Control Zhen Lin Shubhendu Trivedi Cao Xiao Jimeng Sung 25 2 0 02 Feb 2023
Plugin estimators for selective classification with out-of-distribution detection Harikrishna Narasimhan A. Menon Wittawat Jitkrittum Surinder Kumar OODD 28 4 0 29 Jan 2023
Learning to Reject with a Fixed Predictor: Application to Decontextualization Christopher Mohri D. Andor Eunsol Choi Michael Collins BDL 28 22 0 22 Jan 2023
A Trustworthiness Score to Evaluate DNN Predictions Abanoub Ghobrial Darryl Hond Hamid Asgari Kerstin Eder 11 2 0 21 Jan 2023
How to Allocate your Label Budget? Choosing between Active Learning and Learning to Reject in Anomaly Detection Lorenzo Perini Daniele Giannuzzi Jesse Davis 11 2 0 07 Jan 2023