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Can Pretext-Based Self-Supervised Learning Be Boosted by Downstream Data? A Theoretical Analysis.

, , and . AISTATS, volume 151 of Proceedings of Machine Learning Research, page 4198-4216. PMLR, (2022)

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Finding Generalization Measures by Contrasting Signal and Noise., , , , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 33983-34010. PMLR, (2023)Can Pretext-Based Self-Supervised Learning Be Boosted by Downstream Data? A Theoretical Analysis., , and . AISTATS, volume 151 of Proceedings of Machine Learning Research, page 4198-4216. PMLR, (2022)Towards Understanding Generalization via Decomposing Excess Risk Dynamics., , and . ICLR, OpenReview.net, (2022)On Uni-Modal Feature Learning in Supervised Multi-Modal Learning., , , , , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 8632-8656. PMLR, (2023)T-SCI: A Two-Stage Conformal Inference Algorithm with Guaranteed Coverage for Cox-MLP., , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 10203-10213. PMLR, (2021)Towards Understanding Generalization via Decomposing Excess Risk Dynamics., , and . CoRR, (2021)Fighting Fire with Fire: Avoiding DNN Shortcuts through Priming., , , , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 23723-23750. PMLR, (2022)Predictive Inference with Feature Conformal Prediction., , , , , and . ICLR, OpenReview.net, (2023)Benign Overfitting in Classification: Provably Counter Label Noise with Larger Models., , and . ICLR, OpenReview.net, (2023)