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Beyond Separability: Analyzing the Linear Transferability of Contrastive Representations to Related Subpopulations.

, , , and . NeurIPS, (2022)

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Shape Matters: Understanding the Implicit Bias of the Noise Covariance., , , and . COLT, volume 134 of Proceedings of Machine Learning Research, page 2315-2357. PMLR, (2021)Shape Matters: Understanding the Implicit Bias of the Noise Covariance, , , and . (2020)cite arxiv:2006.08680.Connect, Not Collapse: Explaining Contrastive Learning for Unsupervised Domain Adaptation., , , , , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 19847-19878. PMLR, (2022)Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss., , , and . NeurIPS, page 5000-5011. (2021)Diagnosing and Rectifying Vision Models using Language., , , , , and . ICLR, OpenReview.net, (2023)Beyond Positive Scaling: How Negation Impacts Scaling Trends of Language Models., , , , , , and . ACL (Findings), page 7479-7498. Association for Computational Linguistics, (2023)Beyond Separability: Analyzing the Linear Transferability of Contrastive Representations to Related Subpopulations., , , and . NeurIPS, (2022)Amortized Proximal Optimization., , , and . NeurIPS, (2022)Self-supervised Learning is More Robust to Dataset Imbalance., , , and . ICLR, OpenReview.net, (2022)A theoretical study of inductive biases in contrastive learning., and . ICLR, OpenReview.net, (2023)