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Optimizer Benchmarking Needs to Account for Hyperparameter Tuning

, , , , and . (2019)cite arxiv:1910.11758Comment: updated paper, experiments, and writing.

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Multi-Modal Adversarial Autoencoders for Recommendations of Citations and Subject Labels., , , and . CoRR, (2019)HyperMixer: An MLP-based Low Cost Alternative to Transformers., , , , , , and . ACL (1), page 15632-15654. Association for Computational Linguistics, (2023)HyperMixer: An MLP-based Green AI Alternative to Transformers., , , , , , and . CoRR, (2022)Bag-of-Vectors Autoencoders for Unsupervised Conditional Text Generation., and . CoRR, (2021)Plug and Play Autoencoders for Conditional Text Generation., , , , and . EMNLP (1), page 6076-6092. Association for Computational Linguistics, (2020)Learning to Plan for Language Modeling from Unlabeled Data., , and . CoRR, (2024)HyperConformer: Multi-head HyperMixer for Efficient Speech Recognition., , , and . INTERSPEECH, page 2213-2217. ISCA, (2023)Bag-of-Vectors Autoencoders for Unsupervised Conditional Text Generation., and . AACL/IJCNLP (1), page 468-488. Association for Computational Linguistics, (2022)BQ-NCO: Bisimulation Quotienting for Generalizable Neural Combinatorial Optimization., , , , and . CoRR, (2023)Optimizer Benchmarking Needs to Account for Hyperparameter Tuning., , , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 9036-9045. PMLR, (2020)