On Fairness and Calibration

6 September 2017

Papers citing "On Fairness and Calibration"

50 / 184 papers shown

Title
Just Train Twice: Improving Group Robustness without Training Group Information E. Liu Behzad Haghgoo Annie S. Chen Aditi Raghunathan Pang Wei Koh Shiori Sagawa Percy Liang Chelsea Finn OOD 37 540 0 19 Jul 2021
Fairness in Ranking under Uncertainty Ashudeep Singh David Kempe Thorsten Joachims 33 49 0 14 Jul 2021
Calibrating Predictions to Decisions: A Novel Approach to Multi-Class Calibration Shengjia Zhao Michael P. Kim Roshni Sahoo Tengyu Ma Stefano Ermon 20 55 0 12 Jul 2021
Trustworthy AI: A Computational Perspective Haochen Liu Yiqi Wang Wenqi Fan Xiaorui Liu Yaxin Li Shaili Jain Yunhao Liu Anil K. Jain Jiliang Tang FaML 104 197 0 12 Jul 2021
Multi-objective Asynchronous Successive Halving Robin Schmucker Michele Donini Muhammad Bilal Zafar David Salinas Cédric Archambeau 32 24 0 23 Jun 2021
Characterizing the risk of fairwashing Ulrich Aïvodji Hiromi Arai Sébastien Gambs Satoshi Hara 23 27 0 14 Jun 2021
FairCal: Fairness Calibration for Face Verification Tiago Salvador Stephanie Cairns Vikram S. Voleti Noah Marshall Adam M. Oberman FaML 30 19 0 07 Jun 2021
Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning Yuyan Wang Xuezhi Wang Alex Beutel Flavien Prost Jilin Chen Ed H. Chi FaML 27 47 0 04 Jun 2021
Fair Preprocessing: Towards Understanding Compositional Fairness of Data Transformers in Machine Learning Pipeline Sumon Biswas Hridesh Rajan 26 112 0 02 Jun 2021
Bias, Fairness, and Accountability with AI and ML Algorithms Neng-Zhi Zhou Zach Zhang V. Nair Harsh Singhal Jie Chen Agus Sudjianto FaML 21 9 0 13 May 2021
Improving Fairness of AI Systems with Lossless De-biasing Yan Zhou Murat Kantarcioglu Chris Clifton 33 12 0 10 May 2021
Predicting Early Dropout: Calibration and Algorithmic Fairness Considerations Marzieh Karimi-Haghighi Carlos Castillo Davinia Hernández Leo Verónica Moreno Oliver FaML 19 6 0 16 Mar 2021
Local Calibration: Metrics and Recalibration Rachel Luo Aadyot Bhatnagar Yu Bai Shengjia Zhao Huan Wang Caiming Xiong Silvio Savarese Stefano Ermon Edward Schmerling Marco Pavone 27 14 0 22 Feb 2021
On Calibration and Out-of-domain Generalization Yoav Wald Amir Feder D. Greenfeld Uri Shalit OODD 30 153 0 20 Feb 2021
Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information Pranjal Awasthi Alex Beutel Matthaeus Kleindessner Jamie Morgenstern Xuezhi Wang FaML 54 55 0 16 Feb 2021
The Limits of Computation in Solving Equity Trade-Offs in Machine Learning and Justice System Risk Assessment J. Russell FaML 14 0 0 08 Feb 2021
Through the Data Management Lens: Experimental Analysis and Evaluation of Fair Classification Maliha Tashfia Islam Anna Fariha A. Meliou Babak Salimi FaML 30 25 0 18 Jan 2021
Deep Cox Mixtures for Survival Regression Chirag Nagpal Steve Yadlowsky Negar Rostamzadeh Katherine A. Heller CML 44 59 0 16 Jan 2021
Characterizing Fairness Over the Set of Good Models Under Selective Labels Amanda Coston Ashesh Rambachan Alexandra Chouldechova FaML 30 82 0 02 Jan 2021
The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective Naman Goel Alfonso Amayuelas Amit Deshpande Ajay Sharma FaML 41 29 0 21 Dec 2020
Exacerbating Algorithmic Bias through Fairness Attacks Ninareh Mehrabi Muhammad Naveed Fred Morstatter Aram Galstyan AAML 30 67 0 16 Dec 2020
FairBatch: Batch Selection for Model Fairness Yuji Roh Kangwook Lee Steven Euijong Whang Changho Suh VLM 14 128 0 03 Dec 2020
Augmented Fairness: An Interpretable Model Augmenting Decision-Makers' Fairness Tong Wang M. Saar-Tsechansky 31 11 0 17 Nov 2020
Fairness in Biometrics: a figure of merit to assess biometric verification systems Tiago de Freitas Pereira S´ebastien Marcel 24 62 0 04 Nov 2020
AdaFuse: Adaptive Multiview Fusion for Accurate Human Pose Estimation in the Wild Zhe Zhang Chunyu Wang Weichao Qiu Wenhu Qin Wenjun Zeng 3DH 26 87 0 26 Oct 2020
Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information Enyan Dai Suhang Wang FaML 16 241 0 03 Sep 2020
Accuracy and Fairness Trade-offs in Machine Learning: A Stochastic Multi-Objective Approach Suyun Liu Luis Nunes Vicente FaML 29 68 0 03 Aug 2020
An Empirical Characterization of Fair Machine Learning For Clinical Risk Prediction Stephen R. Pfohl Agata Foryciarz N. Shah FaML 33 108 0 20 Jul 2020
A Distributionally Robust Approach to Fair Classification Bahar Taşkesen Viet Anh Nguyen Daniel Kuhn Jose H. Blanchet FaML 28 61 0 18 Jul 2020
Ensuring Fairness Beyond the Training Data Debmalya Mandal Samuel Deng Suman Jana Jeannette M. Wing Daniel J. Hsu FaML OOD 27 58 0 12 Jul 2020
Towards Threshold Invariant Fair Classification Mingliang Chen Min Wu FaML 19 13 0 18 Jun 2020
Individual Calibration with Randomized Forecasting Shengjia Zhao Tengyu Ma Stefano Ermon 16 57 0 18 Jun 2020
Fair Bayesian Optimization Valerio Perrone Michele Donini Muhammad Bilal Zafar Robin Schmucker K. Kenthapadi Cédric Archambeau FaML 27 84 0 09 Jun 2020
Statistical Equity: A Fairness Classification Objective Ninareh Mehrabi Yuzhong Huang Fred Morstatter FaML 20 10 0 14 May 2020
In Pursuit of Interpretable, Fair and Accurate Machine Learning for Criminal Recidivism Prediction Caroline Linjun Wang Bin Han Bhrij Patel Cynthia Rudin FaML HAI 64 84 0 08 May 2020
Ensuring Fairness under Prior Probability Shifts Arpita Biswas Suvam Mukherjee OOD 24 33 0 06 May 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 49 371 0 30 Apr 2020
The Right Tool for the Job: Matching Model and Instance Complexities Roy Schwartz Gabriel Stanovsky Swabha Swayamdipta Jesse Dodge Noah A. Smith 41 168 0 16 Apr 2020
Addressing multiple metrics of group fairness in data-driven decision making M. Miron Songül Tolan Emilia Gómez Carlos Castillo FaML 19 8 0 10 Mar 2020
Counterfactual fairness: removing direct effects through regularization Pietro G. Di Stefano James M. Hickey V. Vasileiou FaML 17 19 0 25 Feb 2020
FR-Train: A Mutual Information-Based Approach to Fair and Robust Training Yuji Roh Kangwook Lee Steven Euijong Whang Changho Suh 24 78 0 24 Feb 2020
Algorithmic Fairness Dana Pessach E. Shmueli FaML 33 386 0 21 Jan 2020
Keeping Community in the Loop: Understanding Wikipedia Stakeholder Values for Machine Learning-Based Systems C. E. Smith Bowen Yu Anjali Srivastava Aaron L Halfaker Loren G. Terveen Haiyi Zhu KELM 21 69 0 14 Jan 2020
Fair Active Learning Hadis Anahideh Abolfazl Asudeh Saravanan Thirumuruganathan FaML 46 51 0 06 Jan 2020
Leveraging Semi-Supervised Learning for Fairness using Neural Networks Vahid Noroozi S. Bahaadini Samira Sheikhi Nooshin Mojab Philip S. Yu 8 7 0 31 Dec 2019
Measuring Non-Expert Comprehension of Machine Learning Fairness Metrics Debjani Saha Candice Schumann Duncan C. McElfresh John P. Dickerson Michelle L. Mazurek Michael Carl Tschantz FaML 32 16 0 17 Dec 2019
Towards Fairer Datasets: Filtering and Balancing the Distribution of the People Subtree in the ImageNet Hierarchy Kaiyu Yang Klint Qinami Li Fei-Fei Jia Deng Olga Russakovsky 21 316 0 16 Dec 2019
Measurement and Fairness Abigail Z. Jacobs Hanna M. Wallach 14 381 0 11 Dec 2019
Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation Zeyu Wang Klint Qinami Yannis Karakozis Kyle Genova P. Nair Kenji Hata Olga Russakovsky 38 357 0 26 Nov 2019
Fairness With Minimal Harm: A Pareto-Optimal Approach For Healthcare Natalia Martínez Martín Bertrán Guillermo Sapiro 19 25 0 16 Nov 2019