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Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time.

M. Wortsman, G. Ilharco, S. Gadre, R. Roelofs, R. Lopes, A. Morcos, H. Namkoong, A. Farhadi, Y. Carmon, S. Kornblith, and L. Schmidt. ICML, volume 162 of Proceedings of Machine Learning Research, page 23965-23998. PMLR, (2022)

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Ludwig Schmidt

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Fast and Sample Near-Optimal Algorithms for Learning Multidimensional Histograms.I. Diakonikolas, J. Li, and L. Schmidt. COLT, volume 75 of Proceedings of Machine Learning Research, page 819-842. PMLR, (2018)On the Fine-Grained Complexity of Empirical Risk Minimization: Kernel Methods and Neural Networks.A. Backurs, P. Indyk, and L. Schmidt. NIPS, page 4308-4318. (2017)Are We Learning Yet? A Meta Review of Evaluation Failures Across Machine Learning.T. Liao, R. Taori, D. Raji, and L. Schmidt. NeurIPS Datasets and Benchmarks, (2021)Differentially Private Learning of Structured Discrete Distributions.I. Diakonikolas, M. Hardt, and L. Schmidt. NIPS, page 2566-2574. (2015)Retiring Adult: New Datasets for Fair Machine Learning.F. Ding, M. Hardt, J. Miller, and L. Schmidt. NeurIPS, page 6478-6490. (2021)Reproducible Scaling Laws for Contrastive Language-Image Learning.M. Cherti, R. Beaumont, R. Wightman, M. Wortsman, G. Ilharco, C. Gordon, C. Schuhmann, L. Schmidt, and J. Jitsev. CVPR, page 2818-2829. IEEE, (2023)Subgroup Robustness Grows On Trees: An Empirical Baseline Investigation.J. Gardner, Z. Popovic, and L. Schmidt. NeurIPS, (2022)Adversarial Scrutiny of Evidentiary Statistical Software.R. Abebe, M. Hardt, A. Jin, J. Miller, L. Schmidt, and R. Wexler. FAccT, page 1733-1746. ACM, (2022)Does progress on ImageNet transfer to real-world datasets?A. Fang, S. Kornblith, and L. Schmidt. CoRR, (2023)Do CIFAR-10 Classifiers Generalize to CIFAR-10?B. Recht, R. Roelofs, L. Schmidt, and V. Shankar. (2018)cite arxiv:1806.00451.

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Disambiguation of "Schmidt, Ludwig"

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Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time.

Please choose a person to relate this publication to

Ludwig Schmidt

Ludwig Schmidt

Ludwig Schmidt

Ludwig Schmidt

Ludwig Schmidt

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Schmidt, Ludwig"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time.

Please choose a person to relate this publication to

Ludwig Schmidt

Ludwig Schmidt

Ludwig Schmidt

Ludwig Schmidt

Ludwig Schmidt

Other publications of authors with the same name

Disambiguation

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URL
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Chicago
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Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time.