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Censoring Representations with an Adversary

18 November 2015

Amos Storkey

Papers citing "Censoring Representations with an Adversary"

50 / 308 papers shown

Title
VAE/WGAN-Based Image Representation Learning For Pose-Preserving Seamless Identity Replacement In Facial ImagesInternational Workshop on Machine Learning for Signal Processing (MLSP), 2019 Hiroki Kawai Jiawei Chen Prakash Ishwar Janusz Konrad GAN CVBM 67 0 0 02 Mar 2020
A Theory of Usable Information Under Computational ConstraintsInternational Conference on Learning Representations (ICLR), 2020 Yilun Xu Shengjia Zhao Jiaming Song Russell Stewart Stefano Ermon 221 193 0 25 Feb 2020
Learning Certified Individually Fair RepresentationsNeural Information Processing Systems (NeurIPS), 2020 Anian Ruoss Mislav Balunović Marc Fischer Martin Vechev FaML 225 104 0 24 Feb 2020
Convex Fairness Constrained Model Using Causal Effect EstimatorsThe Web Conference (WWW), 2020 Hikaru Ogura Akiko Takeda 55 2 0 16 Feb 2020
Case Study: Predictive Fairness to Reduce Misdemeanor Recidivism Through Social Service Interventions Kit T. Rodolfa E. Salomon Lauren Haynes Iván Higuera Mendieta Jamie L Larson Rayid Ghani 111 53 0 24 Jan 2020
Algorithmic Fairness Dana Pessach E. Shmueli FaML 219 413 0 21 Jan 2020
A Review on Generative Adversarial Networks: Algorithms, Theory, and ApplicationsIEEE Transactions on Knowledge and Data Engineering (TKDE), 2020 Jie Gui Zhenan Sun Yonggang Wen Dacheng Tao Jieping Ye EGVM 282 1,008 0 20 Jan 2020
An Adversarial Approach for the Robust Classification of Pneumonia from Chest RadiographsACM Conference on Health, Inference, and Learning (CHIL), 2020 Joseph D. Janizek G. Erion A. DeGrave Su-In Lee OOD MedIm 111 30 0 13 Jan 2020
microbatchGAN: Stimulating Diversity with Multi-Adversarial DiscriminationIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2020 Gonçalo Mordido Haojin Yang Christoph Meinel 98 24 0 10 Jan 2020
Towards Fairer Datasets: Filtering and Balancing the Distribution of the People Subtree in the ImageNet Hierarchy Kaiyu Yang Klint Qinami Li Fei-Fei Gaowen Liu Olga Russakovsky 229 341 0 16 Dec 2019
Towards Fairness in Visual Recognition: Effective Strategies for Bias MitigationComputer Vision and Pattern Recognition (CVPR), 2019 Zeyu Wang Klint Qinami Yannis Karakozis Kyle Genova P. Nair Kenji Hata Olga Russakovsky 321 401 0 26 Nov 2019
Towards Reducing Bias in Gender Classification Komal K. Teru Aishika Chakraborty CVBM FaML 69 3 0 16 Nov 2019
Privacy and Utility Preserving Sensor-Data TransformationsPervasive and Mobile Computing (PMC), 2019 Mohammad Malekzadeh R. Clegg Andrea Cavallaro Hamed Haddadi 89 36 0 14 Nov 2019
Preservation of Anomalous Subgroups On Machine Learning Transformed Data Samuel C. Maina R. Bryant William O. Goal Robert-Florian Samoilescu Kush R. Varshney Komminist Weldemariam 82 0 0 09 Nov 2019
Reducing Sentiment Bias in Language Models via Counterfactual EvaluationFindings (Findings), 2019 Po-Sen Huang Huan Zhang Ray Jiang Robert Stanforth Johannes Welbl Jack W. Rae Vishal Maini Dani Yogatama Pushmeet Kohli 436 232 0 08 Nov 2019
DADI: Dynamic Discovery of Fair Information with Adversarial Reinforcement Learning Michiel A. Bakker Duy Patrick Tu Humberto Riverón Valdés Krishna P. Gummadi Kush R. Varshney Adrian Weller Alex Pentland 203 5 0 30 Oct 2019
Fair Generative Modeling via Weak SupervisionInternational Conference on Machine Learning (ICML), 2019 Kristy Choi Aditya Grover Trisha Singh Rui Shu Stefano Ermon 204 154 0 26 Oct 2019
Optimization Hierarchy for Fair Statistical Decision ProblemsAnnals of Statistics (Ann. Stat.), 2019 A. Aswani Matt Olfat 420 3 0 18 Oct 2019
On the Global Optima of Kernelized Adversarial Representation LearningIEEE International Conference on Computer Vision (ICCV), 2019 Bashir Sadeghi Runyi Yu Vishnu Boddeti AAML 161 33 0 16 Oct 2019
Conditional Learning of Fair RepresentationsInternational Conference on Learning Representations (ICLR), 2019 Han Zhao Amanda Coston T. Adel Geoffrey J. Gordon FaML 236 124 0 16 Oct 2019
Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainabilityNeural Information Processing Systems (NeurIPS), 2019 Christopher Frye C. Rowat Ilya Feige 275 210 0 14 Oct 2019
Constrained Non-Affine Alignment of EmbeddingsIndustrial Conference on Data Mining (IDM), 2019 Yuwei Wang Yan Zheng Yanqing Peng Chin-Chia Michael Yeh Zhongfang Zhuang Das Mahashweta Bendre Mangesh Feifei Li Wei Zhang J. M. Phillips 186 3 0 13 Oct 2019
Generating Fair Universal Representations using Adversarial ModelsIEEE Transactions on Information Forensics and Security (IEEE TIFS), 2019 Peter Kairouz Jiachun Liao Chong Huang Maunil R. Vyas Monica Welfert Lalitha Sankar 484 18 0 27 Sep 2019
Don't Take the Easy Way Out: Ensemble Based Methods for Avoiding Known Dataset BiasesConference on Empirical Methods in Natural Language Processing (EMNLP), 2019 Christopher Clark Mark Yatskar Luke Zettlemoyer OOD 255 498 0 09 Sep 2019
Wasserstein Fair ClassificationConference on Uncertainty in Artificial Intelligence (UAI), 2019 Ray Jiang Aldo Pacchiano T. Stepleton Heinrich Jiang Silvia Chiappa 204 200 0 28 Jul 2019
Adversarial Feature Learning in Brain Interfacing: An Experimental Study on Eliminating Drowsiness EffectsGraz Brain-Computer Interface Conference (GBI), 2019 Ozan Özdenizci B. Oken Tab Memmott M. Fried-Oken Deniz Erdogmus AAML 77 1 0 22 Jul 2019
Training individually fair ML models with Sensitive Subspace RobustnessInternational Conference on Learning Representations (ICLR), 2019 Mikhail Yurochkin Amanda Bower Yuekai Sun FaML OOD 204 122 0 28 Jun 2019
Rényi Fair InferenceInternational Conference on Learning Representations (ICLR), 2019 Sina Baharlouei Maher Nouiehed Ahmad Beirami Meisam Razaviyayn FaML 197 70 0 28 Jun 2019
Learning Fair Representations for Kernel ModelsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 Zilong Tan Samuel Yeom Matt Fredrikson Ameet Talwalkar FaML 202 27 0 27 Jun 2019
Learning Fair and Transferable Representations L. Oneto Michele Donini Andreas Maurer Massimiliano Pontil FaML 282 19 0 25 Jun 2019
Transfer of Machine Learning Fairness across Domains Candice Schumann Xuezhi Wang Alex Beutel Jilin Chen Hai Qian Ed H. Chi 172 72 0 24 Jun 2019
A Cyclically-Trained Adversarial Network for Invariant Representation Learning Jiawei Chen Janusz Konrad Prakash Ishwar AAML GAN OOD 136 8 0 21 Jun 2019
Mitigating Bias in Algorithmic Hiring: Evaluating Claims and Practices Manish Raghavan Solon Barocas Jon M. Kleinberg K. Levy MLAU FaML 253 644 0 21 Jun 2019
Disentangling Influence: Using Disentangled Representations to Audit Model PredictionsNeural Information Processing Systems (NeurIPS), 2019 Charles Marx R. L. Phillips Sorelle A. Friedler C. Scheidegger Suresh Venkatasubramanian TDI CML MLAU 127 27 0 20 Jun 2019
Inherent Tradeoffs in Learning Fair RepresentationsNeural Information Processing Systems (NeurIPS), 2019 Han Zhao Geoffrey J. Gordon FaML 396 233 0 19 Jun 2019
Trade-offs and Guarantees of Adversarial Representation Learning for Information Obfuscation Han Zhao Jianfeng Chi Yuan Tian Geoffrey J. Gordon MIACV 180 2 0 19 Jun 2019
Adversarial training approach for local data debiasing Ulrich Aïvodji F. Bidet Sébastien Gambs Rosin Claude Ngueveu Alain Tapp 173 10 0 19 Jun 2019
Does Object Recognition Work for Everyone? Terrance Devries Ishan Misra Changhan Wang Laurens van der Maaten 280 282 0 06 Jun 2019
Flexibly Fair Representation Learning by DisentanglementInternational Conference on Machine Learning (ICML), 2019 Elliot Creager David Madras J. Jacobsen Marissa A. Weis Kevin Swersky T. Pitassi R. Zemel FaML OOD 380 356 0 06 Jun 2019
Optimized Score Transformation for Consistent Fair ClassificationJournal of machine learning research (JMLR), 2019 Dennis L. Wei Karthikeyan N. Ramamurthy Flavio du Pin Calmon 188 18 0 31 May 2019
On the Fairness of Disentangled RepresentationsNeural Information Processing Systems (NeurIPS), 2019 Francesco Locatello G. Abbati Tom Rainforth Stefan Bauer Bernhard Schölkopf Olivier Bachem FaML DRL 156 238 0 31 May 2019
Overlearning Reveals Sensitive AttributesInternational Conference on Learning Representations (ICLR), 2019 Congzheng Song Vitaly Shmatikov 271 171 0 28 May 2019
ODE Analysis of Stochastic Gradient Methods with Optimism and Anchoring for Minimax Problems Ernest K. Ryu Kun Yuan W. Yin 196 38 0 26 May 2019
Compositional Fairness Constraints for Graph EmbeddingsInternational Conference on Machine Learning (ICML), 2019 A. Bose William L. Hamilton FaML 279 282 0 25 May 2019
Conditional t-SNE: Complementary t-SNE embeddings through factoring out prior information Bo Kang Dario Garcia-Garcia Jefrey Lijffijt Raúl Santos-Rodríguez T. D. Bie 137 4 0 24 May 2019
Learning Fair Representations via an Adversarial Framework Rui Feng Yang Yang Yuehan Lyu Chenhao Tan Luke Huan Chunping Wang FaML 112 59 0 30 Apr 2019
Distributed generation of privacy preserving data with user customization Xiao Chen Thomas Navidi Stefano Ermon Ram Rajagopal 150 11 0 20 Apr 2019
Mitigating Information Leakage in Image Representations: A Maximum Entropy Approach P. Roy Vishnu Boddeti 126 110 0 11 Apr 2019
Revealing Scenes by Inverting Structure from Motion Reconstructions Francesco Pittaluga S. Koppal S. B. Kang Sudipta N. Sinha 3DPC 161 136 0 05 Apr 2019
Optimal Obfuscation Mechanisms via Machine Learning Marco Romanelli K. Chatzikokolakis C. Palamidessi AAML 150 14 0 01 Apr 2019