7 citations · 11 across the 4 of their papers we have counts for
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cs.LG2023
Gathering and Exploiting Higher-Order Information when Training Large Structured Models
Pierre Wolinski
When training large models, such as neural networks, the full derivatives of order 2 and beyond are usually inaccessible, due to their computational cost. Therefore, among the seco…
stat.ML2023★ 7 cited
Efficient Neural Networks for Tiny Machine Learning: A Comprehensive Review
Minh Tri Lê, Pierre Wolinski, Julyan Arbel
The field of Tiny Machine Learning (TinyML) has gained significant attention due to its potential to enable intelligent applications on resource-constrained devices. This review pr…