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Coupling public and private gradient provably helps optimization.

, , , , и . CoRR, (2023)

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Fangxing Zha

Jianing Zha

Tung-sheng Sheng

Tung-sheng Sheng

Tung-sheng Sheng

 

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Dive into Deep Learning for Natural Language Processing., , , , , , и . EMNLP/IJCNLP (2), Association for Computational Linguistics, (2019)Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual., , и . DeepLo@EMNLP-IJCNLP, стр. 132-142. Association for Computational Linguistics, (2019)Differentially Private Optimization on Large Model at Small Cost., , , и . ICML, том 202 из Proceedings of Machine Learning Research, стр. 3192-3218. PMLR, (2023)DEM: Distribution Edited Model for Training with Mixed Data Distributions., , , , и . CoRR, (2024)Differentially Private Bias-Term Fine-tuning of Foundation Models., , , и . ICML, OpenReview.net, (2024)Extreme Miscalibration and the Illusion of Adversarial Robustness., , , , , и . ACL (1), стр. 2500-2525. Association for Computational Linguistics, (2024)On the accuracy and efficiency of group-wise clipping in differentially private optimization., , , , и . CoRR, (2023)Question Type Guided Attention in Visual Question Answering., , , и . ECCV (4), том 11208 из Lecture Notes in Computer Science, стр. 158-175. Springer, (2018)Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing., , , , , и . SustaiNLP@EMNLP, стр. 119-133. Association for Computational Linguistics, (2021)Fine-tuning Language Models for Joint Rewriting and Completion of Code with Potential Bugs., , , , и . ACL (Findings), стр. 15854-15868. Association for Computational Linguistics, (2024)