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Satisfying Real-world Goals with Dataset Constraints

Neural Information Processing Systems (NeurIPS), 2016

24 June 2016

Papers citing "Satisfying Real-world Goals with Dataset Constraints"

50 / 127 papers shown

Title
Private Rate-Constrained Optimization with Applications to Fair Learning Mohammad Yaghini Tudor Cebere Michael Menart A. Bellet Nicolas Papernot 208 0 0 28 May 2025
Fair Supervised Learning Through Constraints on Smooth Nonconvex Unfairness-Measure Surrogates Zahra Khatti Daniel P. Robinson Frank E. Curtis 105 0 0 21 May 2025
Enforcing Fairness Where It Matters: An Approach Based on Difference-of-Convex Constraints Yutian He Yankun Huang Yao Yao Qihang Lin FaML 124 0 0 18 May 2025
Fair Representation Learning for Continuous Sensitive Attributes using Expectation of Integral Probability MetricsIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025 Insung Kong Kunwoong Kim Yongdai Kim FaML 374 4 0 09 May 2025
MAFT: Efficient Model-Agnostic Fairness Testing for Deep Neural Networks via Zero-Order Gradient SearchInternational Conference on Software Engineering (ICSE), 2024 Zhaohui Wang Min Zhang Jingran Yang Bojie Shao Min Zhang 171 7 0 31 Dec 2024
WassFFed: Wasserstein Fair Federated Learning Zhongxuan Han Lulu Zhang C. L. Philip Chen Xiaolin Zheng Fei Zheng Yuyuan Li Yuxiang Cai FedML 141 0 0 11 Nov 2024
Promoting Fairness in Link Prediction with Graph Enhancement Yezi Liu Hanning Chen Mohsen Imani 205 9 0 13 Sep 2024
Multi-Output Distributional Fairness via Post-Processing Gang Li Qihang Lin Ayush Ghosh Tianbao Yang 401 0 0 31 Aug 2024
Neural Lineage Runpeng Yu Xinchao Wang 224 6 0 17 Jun 2024
Back to the Drawing Board for Fair Representation Learning Angeline Pouget Nikola Jovanović Mark Vero Robin Staab Martin Vechev 126 0 0 28 May 2024
A Neurosymbolic Framework for Bias Correction in CNNs Parth Padalkar Natalia Slusarz Ekaterina Komendantskaya Gopal Gupta 195 0 0 24 May 2024
Evaluating Fair Feature Selection in Machine Learning for Healthcare Md. Rahat Shahriar Zawad Peter Washington FaML 219 0 0 28 Mar 2024
Selective Mixup Fine-Tuning for Optimizing Non-Decomposable Objectives Shrinivas Ramasubramanian Harsh Rangwani S. Takemori Kunal Samanta Yuhei Umeda Venkatesh Babu Radhakrishnan 153 1 0 27 Mar 2024
Near-Optimal Solutions of Constrained Learning ProblemsInternational Conference on Learning Representations (ICLR), 2024 Juan Elenter Luiz F. O. Chamon Alejandro Ribeiro 143 8 0 18 Mar 2024
Distribution-Free Fair Federated Learning with Small Samples Qichuan Yin Junzhou Huang Huaxiu Yao Linjun Zhang FedML 291 1 0 25 Feb 2024
Stable Update of Regression Trees Morten Blørstad Berent AA. S. Lunde N. Blaser OOD 121 1 0 21 Feb 2024
Predictive Churn with the Set of Good Models J. Watson-Daniels Flavio du Pin Calmon Alexander DÁmour Carol Xuan Long David C. Parkes Berk Ustun 281 11 0 12 Feb 2024
Strong Duality Relations in Nonconvex Risk-Constrained LearningAnnual Conference on Information Sciences and Systems (CISS), 2023 Dionysis Kalogerias Spyridon Pougkakiotis 143 1 0 02 Dec 2023
Understanding Fairness Surrogate Functions in Algorithmic Fairness Wei Yao Zhanke Zhou Zhicong Li Bo Han Yong Liu 249 7 0 17 Oct 2023
Distilling Influences to Mitigate Prediction Churn in Graph Neural NetworksAsian Conference on Machine Learning (ACML), 2023 Andreas Roth Thomas Liebig 135 0 0 02 Oct 2023
Privacy and Fairness in Federated Learning: on the Perspective of Trade-offACM Computing Surveys (ACM Comput. Surv.), 2023 Huiqiang Chen Tianqing Zhu Tao Zhang Wanlei Zhou Philip S. Yu FedML 188 66 0 25 Jun 2023
Cost-Sensitive Self-Training for Optimizing Non-Decomposable MetricsNeural Information Processing Systems (NeurIPS), 2023 Harsh Rangwani Shrinivas Ramasubramanian S. Takemori Kato Takashi Yuhei Umeda Venkatesh Babu Radhakrishnan 163 4 0 28 Apr 2023
Differentially Private Distributed Convex Optimization Minseok Ryu Kibaek Kim FedML 199 2 0 28 Feb 2023
Within-group fairness: A guidance for more sound between-group fairness Sara Kim Kyusang Yu Yongdai Kim FaML 165 1 0 20 Jan 2023
Calibrated Data-Dependent Constraints with Exact Satisfaction GuaranteesNeural Information Processing Systems (NeurIPS), 2023 Songkai Xue Yuekai Sun Mikhail Yurochkin FaML 113 0 0 15 Jan 2023
Stochastic Methods for AUC Optimization subject to AUC-based Fairness ConstraintsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022 Yao Yao Qihang Lin Tianbao Yang FaML 280 13 0 23 Dec 2022
Towards Understanding Fairness and its Composition in Ensemble Machine LearningInternational Conference on Software Engineering (ICSE), 2022 Usman Gohar Sumon Biswas Hridesh Rajan FaML FedML 145 31 0 08 Dec 2022
Fairness Increases Adversarial Vulnerability Cuong Tran Keyu Zhu Ferdinando Fioretto Pascal Van Hentenryck 173 7 0 21 Nov 2022
A Survey on Preserving Fairness Guarantees in Changing Environments Ainhize Barrainkua Paula Gordaliza Jose A. Lozano Novi Quadrianto FaML 228 3 0 14 Nov 2022
Mitigating Unfairness via Evolutionary Multi-objective Ensemble LearningIEEE Transactions on Evolutionary Computation (TEVC), 2022 Qingquan Zhang Jialin Liu Zeqi Zhang J. Wen Bifei Mao Xin Yao FaML 160 22 0 30 Oct 2022
Omnipredictors for Constrained OptimizationInternational Conference on Machine Learning (ICML), 2022 Lunjia Hu Inbal Livni-Navon Omer Reingold Chutong Yang 206 14 0 15 Sep 2022
Bias Mitigation for Machine Learning Classifiers: A Comprehensive SurveyACM Journal on Responsible Computing (JRC), 2022 Max Hort Zhenpeng Chen Jie M. Zhang Mark Harman Federica Sarro FaML AI4CE 261 230 0 14 Jul 2022
Revealing Unfair Models by Mining Interpretable Evidence Mohit Bajaj Lingyang Chu Vittorio Romaniello Gursimran Singh Jian Pei Zirui Zhou Lanjun Wang Yong Zhang FaML 65 0 0 12 Jul 2022
Input-agnostic Certified Group Fairness via Gaussian Parameter SmoothingInternational Conference on Machine Learning (ICML), 2022 Jiayin Jin Zeru Zhang Yang Zhou Lingfei Wu 172 15 0 22 Jun 2022
FairGrad: Fairness Aware Gradient Descent Gaurav Maheshwari Michaël Perrot FaML 220 12 0 22 Jun 2022
Fairness in Recommendation: Foundations, Methods and ApplicationsACM Transactions on Intelligent Systems and Technology (ACM TIST), 2022 Yunqi Li H. Chen Shuyuan Xu Yingqiang Ge Juntao Tan Shuchang Liu Zelong Li FaML OffRL 388 77 0 26 May 2022
Fair Bayes-Optimal Classifiers Under Predictive ParityNeural Information Processing Systems (NeurIPS), 2022 Xianli Zeng Guang Cheng Guang Cheng FaML 170 17 0 15 May 2022
Are Two Heads the Same as One? Identifying Disparate Treatment in Fair Neural NetworksNeural Information Processing Systems (NeurIPS), 2022 Michael Lohaus Matthäus Kleindessner K. Kenthapadi Francesco Locatello Chris Russell 185 13 0 09 Apr 2022
Representation Bias in Data: A Survey on Identification and Resolution TechniquesACM Computing Surveys (ACM CSUR), 2022 N. Shahbazi Yin Lin Abolfazl Asudeh H. V. Jagadish 240 108 0 22 Mar 2022
Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep ClassifiersComputer Vision and Pattern Recognition (CVPR), 2022 Dominik Zietlow Michael Lohaus Guha Balakrishnan Matthäus Kleindessner Francesco Locatello Bernhard Schölkopf Chris Russell FaML 190 85 0 09 Mar 2022
Bayes-Optimal Classifiers under Group Fairness Xianli Zeng Guang Cheng Guang Cheng FaML 337 24 0 20 Feb 2022
A Lagrangian Duality Approach to Active LearningNeural Information Processing Systems (NeurIPS), 2022 Juan Elenter Navid Naderializadeh Alejandro Ribeiro 305 28 0 08 Feb 2022
SLIDE: a surrogate fairness constraint to ensure fairness consistencyNeural Networks (NN), 2022 Kunwoong Kim Ilsang Ohn Sara Kim Yongdai Kim 177 6 0 07 Feb 2022
Achieving Fairness at No Utility Cost via Data Reweighing with InfluenceInternational Conference on Machine Learning (ICML), 2022 Peizhao Li Hongfu Liu TDI 231 55 0 01 Feb 2022
Model Stability with Continuous Data Updates Huiting Liu Avinesh P.V.S Siddharth Patwardhan Peter Grasch Sachin Agarwal 113 17 0 14 Jan 2022
Fairness-Driven Private Collaborative Machine Learning Dana Pessach Tamir Tassa E. Shmueli FedML 154 8 0 29 Sep 2021
Implicit Rate-Constrained Optimization of Non-decomposable ObjectivesInternational Conference on Machine Learning (ICML), 2021 Abhishek Kumar Harikrishna Narasimhan Andrew Cotter 256 12 0 23 Jul 2021
Automatic Fairness Testing of Neural Classifiers through Adversarial SamplingIEEE Transactions on Software Engineering (TSE), 2021 Peixin Zhang Jingyi Wang Jun Sun Xinyu Wang Guoliang Dong Xingen Wang Ting Dai Jin Song Dong 118 25 0 17 Jul 2021
Training Over-parameterized Models with Non-decomposable ObjectivesNeural Information Processing Systems (NeurIPS), 2021 Harikrishna Narasimhan A. Menon 140 13 0 09 Jul 2021
The Price of Diversity H. Bandi Dimitris Bertsimas 89 0 0 03 Jul 2021