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SOTA2 Research · papers
Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.
| Chidubem Arachie, Bert Huang |
| 2022 |
| arxiv 2202.03987 |
| Learning from Mistakes based on Class Weighting with Application to Neural Architecture Search | Jay Gala, Pengtao Xie | 2021 | arxiv 2112.00275 |
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| MCDAL: Maximum Classifier Discrepancy for Active Learning | Jae Won Cho, Dong-Jin Kim, Yunjae Jung | 2021 | arxiv 2107.11049 |
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| Wisdom of Committees: An Overlooked Approach To Faster and More Accurate Models | Xiaofang Wang, Dan Kondratyuk, Eric Christiansen | 2020 | arxiv 2012.01988 |
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| Deep Learning Reproducibility and Explainable AI (XAI) | A.-M. Leventi-Peetz, T. Östreich | 2022 | arxiv 2202.11452 |
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| Scaling the Wild: Decentralizing Hogwild!-style Shared-memory SGD | Bapi Chatterjee, Vyacheslav Kungurtsev, Dan Alistarh | 2022 | arxiv 2203.06638 |
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| Three things everyone should know about Vision Transformers | Hugo Touvron, Matthieu Cord, Alaaeldin El-Nouby | 2022 | arxiv 2203.09795 |
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| Deep Learning Generalization, Extrapolation, and Over-parameterization | Roozbeh Yousefzadeh | 2022 | arxiv 2203.10366 |
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| Efficient Maximal Coding Rate Reduction by Variational Forms | Christina Baek, Ziyang Wu, Kwan Ho Ryan Chan | 2022 | arxiv 2204.00077 |
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| On the Equity of Nuclear Norm Maximization in Unsupervised Domain Adaptation | Wenju Zhang, Xiang Zhang, Qing Liao | 2022 | arxiv 2204.05596 |
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