mlsanityData to 7 Oct 2026

Invariant Representations through Adversarial Forgetting

arXiv 1911.04060 ↗First posted 11 Nov 2019cs.LG stat.MLcited by 20

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Abstract (arXiv)

We propose a novel approach to achieving invariance for deep neural networks in the form of inducing amnesia to unwanted factors of data through a new adversarial forgetting mechanism. We show that the forgetting mechanism serves as an information-bottleneck, which is manipulated by the adversarial training to learn invariance to unwanted factors. Empirical results show that the proposed framework achieves state-of-the-art performance at learning invariance in both nuisance and bias settings on a diverse collection of datasets and tasks.

Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Nov 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 6; 2022: 5; 2023: 4; 2024: 1; 2025: 3; 2026: 1.

20 papers.

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  1. 2022Bias Mitigation for Machine Learning Classifiers: A Comprehensive Surveycited by 125
  2. 2023A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learningcited by 66
  3. 2021Controllable Guarantees for Fair Outcomes via Contrastive Information Estimationcited by 45
  4. 2021Fair Normalizing Flowscited by 38
  5. 2022Deep Learning on a Healthy Data Diet: Finding Important Examples for Fairnesscited by 21
  6. 2021Attributing Fair Decisions with Attention Interventionscited by 10
  7. 2023Robust Concept Erasure via Kernelized Rate-Distortion Maximizationcited by 10
  8. 2024Fair Bilevel Neural Network (FairBiNN): On Balancing fairness and accuracy via Stackelberg Equilibriumcited by 9
  9. 2023Scalable Infomin Learningcited by 8
  10. 2021Fair Representations by Compressioncited by 7
  11. 2022CAT: Controllable Attribute Translation for Fair Facial Attribute Classificationcited by 6
  12. 2021Information-Theoretic Bias Assessment Of Learned Representations Of Pretrained Face Recognitioncited by 5
8 more
  1. 2021Training Domain-invariant Object Detector Faster with Feature Replay and Slow Learnercited by 2
  2. 2022Distraction is All You Need for Fairnesscited by 2
  3. 2022SoFaiR: Single Shot Fair Representation Learningcited by 1
  4. 2023Learning Fair Representations with High-Confidence Guaranteescited by 1
  5. 2026Nearest-Neighbor Density Estimation for Dependency Suppressioncited by 1
  6. 2025Simple and Effective Specialized Representations for Fair Classifierscited by 0
  7. 2025FairContrast: Enhancing Fairness through Contrastive learning and Customized Augmenting Methods on Tabular Datacited by 0
  8. 2025Fair Representation Learning with Controllable High Confidence Guarantees via Adversarial Inferencecited by 0