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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
Technical Challenges for Training Fair Neural Networks Valeriia Cherepanova V. Nanda Micah Goldblum John P. Dickerson Tom Goldstein FaML 123 28 0 12 Feb 2021
Quantifying and Mitigating Privacy Risks of Contrastive LearningConference on Computer and Communications Security (CCS), 2021 Xinlei He Yang Zhang 247 58 0 08 Feb 2021
Removing biased data to improve fairness and accuracy Sahil Verma Michael Ernst René Just FaML 212 28 0 05 Feb 2021
Adversarial Stylometry in the Wild: Transferable Lexical Substitution Attacks on Author ProfilingConference of the European Chapter of the Association for Computational Linguistics (EACL), 2021 Chris Emmery Ákos Kádár Grzegorz Chrupała AAML 167 21 0 27 Jan 2021
Controllable Guarantees for Fair Outcomes via Contrastive Information EstimationAAAI Conference on Artificial Intelligence (AAAI), 2021 Umang Gupta Aaron Ferber B. Dilkina Greg Ver Steeg 192 70 0 11 Jan 2021
Fairness in Machine Learning L. Oneto Silvia Chiappa FaML 608 534 0 31 Dec 2020
Fundamental Limits and Tradeoffs in Invariant Representation LearningJournal of machine learning research (JMLR), 2020 Han Zhao Chen Dan Bryon Aragam Tommi Jaakkola Geoffrey J. Gordon Pradeep Ravikumar FaML 509 53 0 19 Dec 2020
TARA: Training and Representation Alteration for AI Fairness and Domain GeneralizationNeural Computation (Neural Comput.), 2020 William Paul Armin Hadzic Neil J. Joshi F. Alajaji Philippe Burlina 146 21 0 11 Dec 2020
FairOD: Fairness-aware Outlier DetectionAAAI/ACM Conference on AI, Ethics, and Society (AIES), 2020 Shubhranshu Shekhar Neil Shah Leman Akoglu 239 39 0 05 Dec 2020
Generating private data with user customization Xiao Chen Thomas Navidi Ram Rajagopal 145 2 0 02 Dec 2020
Latent Adversarial Debiasing: Mitigating Collider Bias in Deep Neural Networks L. N. Darlow Stanisław Jastrzębski Amos Storkey 184 26 0 19 Nov 2020
Metric-Free Individual Fairness with Cooperative Contextual BanditsIndustrial Conference on Data Mining (IDM), 2020 Qian Hu Huzefa Rangwala FaML 149 11 0 13 Nov 2020
All of the Fairness for Edge Prediction with Optimal TransportInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2020 Charlotte Laclau I. Redko Manvi Choudhary C. Largeron FaML 170 49 0 30 Oct 2020
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial RobustnessProceedings of the IEEE (Proc. IEEE), 2020 Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 328 50 0 19 Oct 2020
Environment Inference for Invariant Learning Elliot Creager J. Jacobsen R. Zemel OOD 658 431 0 14 Oct 2020
Measuring and Reducing Gendered Correlations in Pre-trained Models Kellie Webster Xuezhi Wang Ian Tenney Alex Beutel Emily Pitler Ellie Pavlick Jilin Chen Ed Chi Slav Petrov FaML 452 295 0 12 Oct 2020
FairMixRep : Self-supervised Robust Representation Learning for Heterogeneous Data with Fairness constraints Souradip Chakraborty Ekansh Verma Saswata Sahoo J. Datta 120 4 0 07 Oct 2020
Fairness Perception from a Network-Centric Perspective Farzan Masrour P. Tan A. Esfahanian FaML 105 2 0 07 Oct 2020
Can we Generalize and Distribute Private Representation Learning?International Conference on Artificial Intelligence and Statistics (AISTATS), 2020 Sheikh Shams Azam Taejin Kim Seyyedali Hosseinalipour Carlee Joe-Wong S. Bagchi Christopher G. Brinton 233 12 0 05 Oct 2020
Fairness in Machine Learning: A SurveyACM Computing Surveys (ACM CSUR), 2020 Simon Caton C. Haas FaML 497 789 0 04 Oct 2020
Universal Physiological Representation Learning with Soft-Disentangled Rateless Autoencoders Mo Han Ozan Özdenizci T. Koike-Akino Ye Wang Deniz Erdogmus OOD AAML DRL 194 11 0 28 Sep 2020
Differentially Private and Fair Deep Learning: A Lagrangian Dual ApproachAAAI Conference on Artificial Intelligence (AAAI), 2020 Cuong Tran Ferdinando Fioretto Pascal Van Hentenryck FedML 144 87 0 26 Sep 2020
Subverting Privacy-Preserving GANs: Hiding Secrets in Sanitized ImagesAAAI Conference on Artificial Intelligence (AAAI), 2020 Kang Liu Benjamin Tan S. Garg PICV 99 7 0 19 Sep 2020
Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute InformationWeb Search and Data Mining (WSDM), 2020 Enyan Dai Suhang Wang FaML 330 297 0 03 Sep 2020
NoPeek: Information leakage reduction to share activations in distributed deep learning Praneeth Vepakomma Abhishek Singh O. Gupta Ramesh Raskar MIACV FedML 210 102 0 20 Aug 2020
Null-sampling for Interpretable and Fair RepresentationsEuropean Conference on Computer Vision (ECCV), 2020 T. Kehrenberg Myles Bartlett Oliver Thomas Novi Quadrianto OOD 97 30 0 12 Aug 2020
$Beyond $\mathcal{H}$-Divergence: Domain Adaptation Theory With Jensen-Shannon Divergence$ Beyond $\mathcal{H}$ -Divergence: Domain Adaptation Theory With Jensen-Shannon Divergence Changjian Shui Qi Chen Jun Wen Fan Zhou Christian Gagné Boyu Wang 161 24 0 30 Jul 2020
Fairness-Aware Online Personalization G. R. Lal S. Geyik K. Kenthapadi FaML 141 4 0 30 Jul 2020
Privacy-preserving Voice Analysis via Disentangled Representations Ranya Aloufi Hamed Haddadi David E. Boyle DRL 284 62 0 29 Jul 2020
A Distributionally Robust Approach to Fair Classification Bahar Taşkesen Viet Anh Nguyen Daniel Kuhn Jose H. Blanchet FaML 200 66 0 18 Jul 2020
Representation via Representations: Domain Generalization via Adversarially Learned Invariant Representations Zhun Deng Frances Ding Cynthia Dwork Rachel Hong Giovanni Parmigiani Prasad Patil Pragya Sur OOD FaML 115 33 0 20 Jun 2020
Adversarial representation learning for private speech generation David Ericsson Adam Östberg Edvin Listo Zec John Martinsson Olof Mogren 128 18 0 16 Jun 2020
Learning Smooth and Fair Representations Xavier Gitiaux Huzefa Rangwala FaML 122 16 0 15 Jun 2020
Adversarial representation learning for synthetic replacement of private attributes John Martinsson Edvin Listo Zec D. Gillblad Olof Mogren PICV 212 9 0 14 Jun 2020
Disentanglement for Discriminative Visual Recognition Xiaofeng Liu DRL 173 6 0 14 Jun 2020
Privacy Adversarial Network: Representation Learning for Mobile Data Privacy Sicong Liu Junzhao Du Anshumali Shrivastava Lin Zhong 191 16 0 08 Jun 2020
Review of Mathematical frameworks for Fairness in Machine Learning E. del Barrio Paula Gordaliza Jean-Michel Loubes FaML FedML 120 43 0 26 May 2020
Demoting Racial Bias in Hate Speech DetectionInternational Workshop on Natural Language Processing for Social Media (NLPSM), 2020 Mengzhou Xia Anjalie Field Yulia Tsvetkov 192 132 0 25 May 2020
An analysis on the use of autoencoders for representation learning: fundamentals, learning task case studies, explainability and challenges D. Charte F. Charte M. J. D. Jesus Francisco Herrera SSL OOD 187 60 0 21 May 2020
Reducing Overlearning through Disentangled Representations by Suppressing Unknown Tasks Naveen Panwar Tarun Tater A. Sankaran Senthil Mani VLM 89 1 0 20 May 2020
Ethical Adversaries: Towards Mitigating Unfairness with Adversarial Machine Learning Pieter Delobelle Paul Temple Gilles Perrouin Benoit Frénay P. Heymans Bettina Berendt AAML FaML 223 19 0 14 May 2020
Disentangled Adversarial Transfer Learning for Physiological BiosignalsAnnual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2020 Mo Han Ozan Özdenizci Ye Wang T. Koike-Akino Deniz Erdogmus OOD AAML 65 6 0 15 Apr 2020
Fingerprint Presentation Attack Detection: A Sensor and Material Agnostic Approach Steven A. Grosz T. Chugh Anil K. Jain AAML OOD 120 29 0 06 Apr 2020
FairNN- Conjoint Learning of Fair Representations for Fair DecisionsIFIP Working Conference on Database Semantics (IWDS), 2020 Tongxin Hu Vasileios Iosifidis Wentong Liao Hang Zhang M. Yang Eirini Ntoutsi Bodo Rosenhahn FaML 152 19 0 05 Apr 2020
Abstracting Fairness: Oracles, Metrics, and InterpretabilitySymposium on Foundations of Responsible Computing (FRC), 2020 Cynthia Dwork Christina Ilvento G. Rothblum Pragya Sur FaML 141 8 0 04 Apr 2020
Information Leakage in Embedding ModelsConference on Computer and Communications Security (CCS), 2020 Congzheng Song A. Raghunathan MIACV 385 320 0 31 Mar 2020
DYSAN: Dynamically sanitizing motion sensor data against sensitive inferences through adversarial networksACM Asia Conference on Computer and Communications Security (AsiaCCS), 2020 Claude Rosin Ngueveu A. Boutet Carole Frindel Sébastien Gambs T. Jourdan Claude Rosin Ngueveu 134 30 0 23 Mar 2020
Fairness by Learning Orthogonal Disentangled RepresentationsEuropean Conference on Computer Vision (ECCV), 2020 Mhd Hasan Sarhan Nassir Navab Abouzar Eslami Shadi Albarqouni FaML OOD CML 220 108 0 12 Mar 2020
Hurtful Words: Quantifying Biases in Clinical Contextual Word EmbeddingsACM Conference on Health, Inference, and Learning (CHIL), 2020 H. Zhang Amy X. Lu Mohamed Abdalla Matthew B. A. McDermott Marzyeh Ghassemi 226 195 0 11 Mar 2020
Addressing target shift in zero-shot learning using grouped adversarial learning Saneem A. Chemmengath Soumava Paul Samarth Bharadwaj Suranjana Samanta Karthik Sankaranarayanan VLM 123 1 0 02 Mar 2020