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Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution.

, , , , и . ICLR, OpenReview.net, (2022)

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Training Classifiers with Natural Language Explanations, , , , , и . arXiv preprint arXiv:1805.03818, (2018)Pre-training Graph Neural Networks., , , , , , и . CoRR, (2019)Learning Where to Sample in Structured Prediction., , и . AISTATS, том 38 из JMLR Workshop and Conference Proceedings, JMLR.org, (2015)Estimation from Indirect Supervision with Linear Moments., , , и . ICML, том 48 из JMLR Workshop and Conference Proceedings, стр. 2568-2577. JMLR.org, (2016)A Hitting Time Analysis of Stochastic Gradient Langevin Dynamics., , и . COLT, том 65 из Proceedings of Machine Learning Research, стр. 1980-2022. PMLR, (2017)Learning Programs: A Hierarchical Bayesian Approach., , и . ICML, стр. 639-646. Omnipress, (2010)Fairness Without Demographics in Repeated Loss Minimization., , , и . ICML, том 80 из Proceedings of Machine Learning Research, стр. 1934-1943. PMLR, (2018)Stronger Data Poisoning Attacks Break Data Sanitization Defenses., , и . CoRR, (2018)GreaseLM: Graph REASoning Enhanced Language Models, , , , , , и . International Conference on Learning Representations, (2021)Strategies for Pre-training Graph Neural Networks, , , , , , и . (2019)cite arxiv:1905.12265Comment: Accepted as a spotlight to ICLR 2020.