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Doha Hwang

Alumni

Publications

Can We Scale Transformers to Predict Parameters of Diverse ImageNet Models?
Boris Knyazev
Doha Hwang
Simon Lacoste-Julien
2023-07-03
Proceedings of the 40th International Conference on Machine Learning (publié)
doi.org
openreview.net
Can We Scale Transformers to Predict Parameters of Diverse ImageNet Models?
Boris Knyazev
Doha Hwang
Simon Lacoste-Julien
Pretraining a neural network on a large dataset is becoming a cornerstone in machine learning that is within the reach of only a few communi… (voir plus)ties with large-resources. We aim at an ambitious goal of democratizing pretraining. Towards that goal, we train and release a single neural network that can predict high quality ImageNet parameters of other neural networks. By using predicted parameters for initialization we are able to boost training of diverse ImageNet models available in PyTorch. When transferred to other datasets, models initialized with predicted parameters also converge faster and reach competitive final performance.
2023-04-24
ICML.cc/2023/Conference (poster)
doi.org
openreview.net
Can We Scale Transformers to Predict Parameters of Diverse ImageNet Models?
Boris Knyazev
Doha Hwang
Simon Lacoste-Julien
Pretraining a neural network on a large dataset is becoming a cornerstone in machine learning that is within the reach of only a few communi… (voir plus)ties with large-resources. We aim at an ambitious goal of democratizing pretraining. Towards that goal, we train and release a single neural network that can predict high quality ImageNet parameters of other neural networks. By using predicted parameters for initialization we are able to boost training of diverse ImageNet models available in PyTorch. When transferred to other datasets, models initialized with predicted parameters also converge faster and reach competitive final performance.
2023-03-07
ArXiv (prépublication)
doi.org
arxiv.org