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Controllable Invariance through Adversarial Feature Learning
v1v2v3 (latest)

Controllable Invariance through Adversarial Feature Learning

Neural Information Processing Systems (NeurIPS), 2017
31 May 2017
Qizhe Xie
Zihang Dai
Yulun Du
Eduard H. Hovy
Graham Neubig
    OOD
ArXiv (abs)PDFHTML

Papers citing "Controllable Invariance through Adversarial Feature Learning"

50 / 190 papers shown
Title
Fair Representation Learning with Controllable High Confidence Guarantees via Adversarial Inference
Fair Representation Learning with Controllable High Confidence Guarantees via Adversarial Inference
Yuhong Luo
Austin Hoag
Xintong Wang
Philip S Thomas
Przemyslaw A. Grabowicz
FaML
237
0
0
23 Oct 2025
Training Feature Attribution for Vision Models
Training Feature Attribution for Vision Models
Aziz Bacha
Thomas George
TDIFAtt
260
0
0
10 Oct 2025
PolyJuice Makes It Real: Black-Box, Universal Red Teaming for Synthetic Image Detectors
PolyJuice Makes It Real: Black-Box, Universal Red Teaming for Synthetic Image Detectors
Sepehr Dehdashtian
Mashrur M. Morshed
Jacob H. Seidman
Gaurav Bharaj
Vishnu Boddeti
AAMLDiffM
88
0
0
19 Sep 2025
Contrastive Representations for Temporal Reasoning
Contrastive Representations for Temporal Reasoning
Alicja Ziarko
Michal Bortkiewicz
Michal Zawalski
Benjamin Eysenbach
Piotr Milos
NAI
118
2
0
18 Aug 2025
Steering Out-of-Distribution Generalization with Concept Ablation Fine-Tuning
Steering Out-of-Distribution Generalization with Concept Ablation Fine-Tuning
Helena Casademunt
Caden Juang
Adam Karvonen
Samuel Marks
Senthooran Rajamanoharan
Neel Nanda
OODDLLMSV
308
9
0
22 Jul 2025
Preserving Task-Relevant Information Under Linear Concept Removal
Preserving Task-Relevant Information Under Linear Concept Removal
Floris Holstege
Shauli Ravfogel
Bram Wouters
KELM
325
0
0
12 Jun 2025
Fairness-aware Anomaly Detection via Fair Projection
Fairness-aware Anomaly Detection via Fair Projection
Feng Xiao
Xiaoying Tang
Jicong Fan
244
0
0
16 May 2025
ReLU integral probability metric and its applications
ReLU integral probability metric and its applications
Yuha Park
Kunwoong Kim
Insung Kong
Yongdai Kim
251
0
0
26 Apr 2025
Fundamental Limits of Perfect Concept Erasure
Fundamental Limits of Perfect Concept ErasureInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2025
Somnath Basu Roy Chowdhury
Avinava Dubey
Ahmad Beirami
Rahul Kidambi
Nicholas Monath
Amr Ahmed
Snigdha Chaturvedi
234
3
0
25 Mar 2025
Debiasing Diffusion Model: Enhancing Fairness through Latent Representation Learning in Stable Diffusion Model
Debiasing Diffusion Model: Enhancing Fairness through Latent Representation Learning in Stable Diffusion Model
Lin-Chun Huang
Ching Chieh Tsao
Fang Su
Jung-Hsien Chiang
241
4
0
16 Mar 2025
Diffusing DeBias: Synthetic Bias Amplification for Model Debiasing
Diffusing DeBias: Synthetic Bias Amplification for Model Debiasing
Massimiliano Ciranni
Vito Paolo Pastore
Roberto Di Via
Enzo Tartaglione
Francesca Odone
Vittorio Murino
DiffM
387
0
0
13 Feb 2025
MaskMedPaint: Masked Medical Image Inpainting with Diffusion Models for
  Mitigation of Spurious Correlations
MaskMedPaint: Masked Medical Image Inpainting with Diffusion Models for Mitigation of Spurious Correlations
Qixuan Jin
Walter Gerych
Elisa Kreiss
DiffMMedIm
157
2
0
16 Nov 2024
Alpha and Prejudice: Improving $α$-sized Worst-case Fairness via
  Intrinsic Reweighting
Alpha and Prejudice: Improving ααα-sized Worst-case Fairness via Intrinsic ReweightingIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2024
Jing Li
Yinghua Yao
Yuangang Pan
Xuanqian Wang
Ivor Tsang
Xiuju Fu
FaML
261
0
0
05 Nov 2024
Power side-channel leakage localization through adversarial training of
  deep neural networks
Power side-channel leakage localization through adversarial training of deep neural networks
Jimmy Gammell
A. Raghunathan
Kaushik Roy
AAML
201
0
0
29 Oct 2024
A Different Level Text Protection Mechanism With Differential Privacy
A Different Level Text Protection Mechanism With Differential Privacy
Qingwen Fu
153
0
0
05 Sep 2024
Multi-Output Distributional Fairness via Post-Processing
Multi-Output Distributional Fairness via Post-Processing
Gang Li
Qihang Lin
Ayush Ghosh
Tianbao Yang
429
0
0
31 Aug 2024
Say My Name: a Model's Bias Discovery Framework
Say My Name: a Model's Bias Discovery Framework
Massimiliano Ciranni
Luca Molinaro
C. Barbano
Attilio Fiandrotti
Vittorio Murino
Vito Paolo Pastore
Enzo Tartaglione
196
4
0
18 Aug 2024
Fairness and Bias Mitigation in Computer Vision: A Survey
Fairness and Bias Mitigation in Computer Vision: A Survey
Sepehr Dehdashtian
Ruozhen He
Yi Li
Guha Balakrishnan
Nuno Vasconcelos
Vicente Ordonez
Vishnu Boddeti
309
11
0
05 Aug 2024
10 Years of Fair Representations: Challenges and Opportunities
10 Years of Fair Representations: Challenges and Opportunities
Mattia Cerrato
Marius Köppel
Philipp Wolf
Stefan Kramer
FaML
173
6
0
04 Jul 2024
Provable Optimization for Adversarial Fair Self-supervised Contrastive
  Learning
Provable Optimization for Adversarial Fair Self-supervised Contrastive Learning
Qi Qi
Quanqi Hu
Qihang Lin
Tianbao Yang
265
3
0
09 Jun 2024
Single-loop Stochastic Algorithms for Difference of Max-Structured
  Weakly Convex Functions
Single-loop Stochastic Algorithms for Difference of Max-Structured Weakly Convex Functions
Quanqi Hu
Qi Qi
Zhaosong Lu
Tianbao Yang
338
3
0
28 May 2024
Back to the Drawing Board for Fair Representation Learning
Back to the Drawing Board for Fair Representation Learning
Angeline Pouget
Nikola Jovanović
Mark Vero
Robin Staab
Martin Vechev
130
0
0
28 May 2024
Utility-Fairness Trade-Offs and How to Find Them
Utility-Fairness Trade-Offs and How to Find Them
Sepehr Dehdashtian
Bashir Sadeghi
Vishnu Boddeti
175
15
0
15 Apr 2024
From Discrete to Continuous: Deep Fair Clustering With Transferable
  Representations
From Discrete to Continuous: Deep Fair Clustering With Transferable Representations
Xiang Zhang
233
0
0
24 Mar 2024
Pooling Image Datasets With Multiple Covariate Shift and Imbalance
Sotirios Panagiotis Chytas
Vishnu Suresh Lokhande
Peiran Li
Vikas Singh
OOD
262
1
0
05 Mar 2024
Disentangling representations of retinal images with generative models
Disentangling representations of retinal images with generative models
Sarah Muller
Lisa M. Koch
Hendrik P. A. Lensch
Philipp Berens
MedIm
287
4
0
29 Feb 2024
Explaining Text Classifiers with Counterfactual Representations
Explaining Text Classifiers with Counterfactual Representations
Pirmin Lemberger
Antoine Saillenfest
233
2
0
01 Feb 2024
Prompt Optimization via Adversarial In-Context Learning
Prompt Optimization via Adversarial In-Context LearningAnnual Meeting of the Association for Computational Linguistics (ACL), 2023
Do Xuan Long
Yiran Zhao
Hannah Brown
Yuxi Xie
James Xu Zhao
Nancy F. Chen
Kenji Kawaguchi
Michael Qizhe Xie
Junxian He
345
26
0
05 Dec 2023
Causal Fairness-Guided Dataset Reweighting using Neural Networks
Causal Fairness-Guided Dataset Reweighting using Neural Networks
Xuan Zhao
Klaus Broelemann
Salvatore Ruggieri
Gjergji Kasneci
204
1
0
17 Nov 2023
Fair Supervised Learning with A Simple Random Sampler of Sensitive
  Attributes
Fair Supervised Learning with A Simple Random Sampler of Sensitive AttributesInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Jinwon Sohn
Qifan Song
Guang Lin
FaML
252
1
0
10 Nov 2023
Invariance Measures for Neural Networks
Invariance Measures for Neural NetworksApplied Soft Computing (ASC), 2022
F. Quiroga
J. Torrents-Barrena
Laura Lanzarini
Domenec Puig-Valls
94
4
0
26 Oct 2023
Learning Fair Representations with High-Confidence Guarantees
Learning Fair Representations with High-Confidence Guarantees
Yuhong Luo
Austin Hoag
Philip S Thomas
FaMLAI4TS
325
1
0
23 Oct 2023
A Novel Information-Theoretic Objective to Disentangle Representations
  for Fair Classification
A Novel Information-Theoretic Objective to Disentangle Representations for Fair ClassificationInternational Joint Conference on Natural Language Processing (IJCNLP), 2023
Pierre Colombo
Nathan Noiry
Guillaume Staerman
Pablo Piantanida
FaMLDRL
235
2
0
21 Oct 2023
AI-based association analysis for medical imaging using latent-space geometric confounder correction
AI-based association analysis for medical imaging using latent-space geometric confounder correction
Xianjing Liu
Yue Liu
Meike W. Vernooij
E. Wolvius
Gennady V. Roshchupkin
Esther E. Bron
MedIm
253
2
0
03 Oct 2023
Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda
  for Developing Practical Guidelines and Tools
Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and ToolsConference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO), 2023
Maximilian Schambach
Rakshit Naidu
Rayid Ghani
Kit T. Rodolfa
Daniel E. Ho
Hoda Heidari
FaML
233
21
0
29 Sep 2023
Towards Poisoning Fair Representations
Towards Poisoning Fair RepresentationsInternational Conference on Learning Representations (ICLR), 2023
Tianci Liu
Haoyu Wang
Feijie Wu
Hengtong Zhang
Pan Li
Lu Su
Jing Gao
AAML
153
3
0
28 Sep 2023
SOAR: Scene-debiasing Open-set Action Recognition
SOAR: Scene-debiasing Open-set Action RecognitionIEEE International Conference on Computer Vision (ICCV), 2023
Yuanhao Zhai
Ziyi Liu
Zhenyu Wu
Yi Wu
Chunluan Zhou
David Doermann
Junsong Yuan
Gang Hua
242
13
0
03 Sep 2023
LEACE: Perfect linear concept erasure in closed form
LEACE: Perfect linear concept erasure in closed formNeural Information Processing Systems (NeurIPS), 2023
Nora Belrose
David Schneider-Joseph
Shauli Ravfogel
Robert Bamler
Edward Raff
Stella Biderman
KELMMU
657
163
0
06 Jun 2023
Shielded Representations: Protecting Sensitive Attributes Through
  Iterative Gradient-Based Projection
Shielded Representations: Protecting Sensitive Attributes Through Iterative Gradient-Based ProjectionAnnual Meeting of the Association for Computational Linguistics (ACL), 2023
Shadi Iskander
Kira Radinsky
Yonatan Belinkov
298
25
0
17 May 2023
FLAC: Fairness-Aware Representation Learning by Suppressing
  Attribute-Class Associations
FLAC: Fairness-Aware Representation Learning by Suppressing Attribute-Class AssociationsIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
Ioannis Sarridis
C. Koutlis
Symeon Papadopoulos
Christos Diou
153
14
0
27 Apr 2023
Efficient fair PCA for fair representation learning
Efficient fair PCA for fair representation learningInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Matthäus Kleindessner
Michele Donini
Chris Russell
Muhammad Bilal Zafar
FaML
147
26
0
26 Feb 2023
Scalable Infomin Learning
Scalable Infomin LearningNeural Information Processing Systems (NeurIPS), 2023
Yanzhi Chen
Wei-Der Sun
Yingzhen Li
Adrian Weller
221
9
0
21 Feb 2023
Parameter-efficient Modularised Bias Mitigation via AdapterFusion
Parameter-efficient Modularised Bias Mitigation via AdapterFusionConference of the European Chapter of the Association for Computational Linguistics (EACL), 2023
Deepak Kumar
Oleg Lesota
George Zerveas
Daniel Cohen
Carsten Eickhoff
Markus Schedl
Navid Rekabsaz
MoMeKELM
216
33
0
13 Feb 2023
On the Alignment of Group Fairness with Attribute Privacy
On the Alignment of Group Fairness with Attribute PrivacyWISE (WISE), 2022
Jan Aalmoes
Vasisht Duddu
A. Boutet
210
5
0
18 Nov 2022
MMD-B-Fair: Learning Fair Representations with Statistical Testing
MMD-B-Fair: Learning Fair Representations with Statistical TestingInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Namrata Deka
Danica J. Sutherland
209
12
0
15 Nov 2022
Unbiased Supervised Contrastive Learning
Unbiased Supervised Contrastive LearningInternational Conference on Learning Representations (ICLR), 2022
C. Barbano
Benoit Dufumier
Enzo Tartaglione
Marco Grangetto
Pietro Gori
FaMLSSL
172
42
0
10 Nov 2022
Log-linear Guardedness and its Implications
Log-linear Guardedness and its ImplicationsAnnual Meeting of the Association for Computational Linguistics (ACL), 2022
Shauli Ravfogel
Yoav Goldberg
Robert Bamler
609
2
0
18 Oct 2022
FARE: Provably Fair Representation Learning with Practical Certificates
FARE: Provably Fair Representation Learning with Practical CertificatesInternational Conference on Machine Learning (ICML), 2022
Nikola Jovanović
Mislav Balunović
Dimitar I. Dimitrov
Martin Vechev
305
20
0
13 Oct 2022
MEDFAIR: Benchmarking Fairness for Medical Imaging
MEDFAIR: Benchmarking Fairness for Medical ImagingInternational Conference on Learning Representations (ICLR), 2022
Yongshuo Zong
Yongxin Yang
Timothy M. Hospedales
OOD
243
85
0
04 Oct 2022
Improving Image Clustering through Sample Ranking and Its Application to
  remote--sensing images
Improving Image Clustering through Sample Ranking and Its Application to remote--sensing imagesRemote Sensing (RS), 2022
Qing Li
Guoping Qiu
170
2
0
26 Sep 2022
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