Contrastive learning



Not quite sure what to do with this incredible and no-longer-appropriate-for-promotions band photo, but wow, what a time capsule.

References

Balestriero, Randall, Mark Ibrahim, Vlad Sobal, Ari Morcos, Shashank Shekhar, Tom Goldstein, Florian Bordes, et al. 2023. β€œA Cookbook of Self-Supervised Learning.” arXiv.
Chehab, Omar, Alexandre Gramfort, and Aapo Hyvarinen. 2022. β€œThe Optimal Noise in Noise-Contrastive Learning Is Not What You Think.” arXiv:2203.01110 [Cs, Stat], March.
Gutmann, Michael U., and Aapo HyvΓ€rinen. 2012. β€œNoise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics.” Journal of Machine Learning Research 13 (11): 307–61.
Gutmann, Michael, and Aapo Hyvarinen. n.d. β€œNoise-Contrastive Estimation: A New Estimation Principle for Unnormalized Statistical Models,” 8.
Hinton, Geoffrey E. 2002. β€œTraining Products of Experts by Minimizing Contrastive Divergence.” Neural Computation 14 (8): 1771–1800.
Le-Khac, Phuc H., Graham Healy, and Alan F. Smeaton. 2020. β€œContrastive Representation Learning: A Framework and Review.” IEEE Access 8: 193907–34.
Ma, Zhuang, and Michael Collins. 2018. β€œNoise Contrastive Estimation and Negative Sampling for Conditional Models: Consistency and Statistical Efficiency.” arXiv:1809.01812 [Cs, Stat], September.
Miller, Benjamin Kurt, Christoph Weniger, and Patrick ForrΓ©. 2022. β€œContrastive Neural Ratio Estimation.” In.
Oord, Aaron van den, Yazhe Li, and Oriol Vinyals. 2019. β€œRepresentation Learning with Contrastive Predictive Coding.” arXiv.
Saunshi, Nikunj, Jordan Ash, Surbhi Goel, Dipendra Misra, Cyril Zhang, Sanjeev Arora, Sham Kakade, and Akshay Krishnamurthy. 2022. β€œUnderstanding Contrastive Learning Requires Incorporating Inductive Biases.” arXiv:2202.14037 [Cs], February.
Smith, Noah A., and Jason Eisner. 2005. β€œContrastive Estimation: Training Log-Linear Models on Unlabeled Data.” In Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics - ACL ’05, 354–62. Ann Arbor, Michigan: Association for Computational Linguistics.
Zhang, Yifei, Hao Zhu, Zixing Song, Piotr Koniusz, and Irwin King. 2022. β€œCOSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning.” In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2524–34. Washington DC USA: ACM.
Zhu, Hao, Ke Sun, and Piotr Koniusz. 2022. β€œContrastive Laplacian Eigenmaps.” arXiv.

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