%Aigaion2 BibTeX export from Idiap Publications
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@INPROCEEDINGS{Sivaprasad_ICML2020_2020,
         author = {Sivaprasad, Prabhu Teja and Mai, Florian and Vogels, Thijs and Jaggi, Martin and Fleuret, Francois},
       keywords = {Benchmarking, Hyperparameter optimization, optimization},
       projects = {Idiap},
          title = {Optimizer Benchmarking Needs to Account for Hyperparameter Tuning},
      booktitle = {Proceedings of the 37th International Conference on Machine Learning},
           year = {2020},
       location = {Vienna, Austria},
            url = {https://icml.cc/Conferences/2020/Schedule?showEvent=6589},
       crossref = {Sivaprasad_Idiap-RR-19-2019},
       abstract = {The performance of optimizers, particularly in deep learning, depends considerably on their chosen hyperparameter configuration. The efficacy of optimizers is often studied under near-optimal problem-specific hyperparameters, and finding these settings may be prohibitively costly for practitioners. In this work, we argue that a fair assessment of optimizers' performance must take the computational cost of hyperparameter tuning into account, i.e., how easy it is to find good hyperparameter configurations using an automatic hyperparameter search. Evaluating a variety of optimizers on an extensive set of standard datasets and architectures, our results indicate that Adam is the most practical solution, particularly in low-budget scenarios.},
            pdf = {https://publications.idiap.ch/attachments/papers/2020/Sivaprasad_ICML2020_2020.pdf}
}



crossreferenced publications: 
@TECHREPORT{Sivaprasad_Idiap-RR-19-2019,
         author = {Sivaprasad, Prabhu Teja and Mai, Florian and Vogels, Thijs and Jaggi, Martin and Fleuret, Francois},
       keywords = {Benchmarking, Hyperparameter optimization, optimization},
       projects = {Idiap},
          month = {12},
          title = {On the Tunability of Optimizers in Deep Learning},
           type = {Idiap-RR},
         number = {Idiap-RR-19-2019},
           year = {2019},
    institution = {Idiap},
           note = {Under review at ICLR 2020},
            url = {https://arxiv.org/abs/1910.11758},
            pdf = {https://publications.idiap.ch/attachments/reports/2019/Sivaprasad_Idiap-RR-19-2019.pdf}
}