[HTML][HTML] The unreasonable effectiveness of early discarding after one epoch in neural network hyperparameter optimization
To reach high performance with deep learning, hyperparameter optimization (HPO) is
essential. This process is usually time-consuming due to costly evaluations of neural …
essential. This process is usually time-consuming due to costly evaluations of neural …
Optimization of Learning Workflows at Large Scale on High-Performance Computing Systems
R Egele - 2024 - theses.hal.science
In the past decade, machine learning has experienced exponential growth, propelled by
abundant datasets, algorithmic advancements, and increased computational power …
abundant datasets, algorithmic advancements, and increased computational power …
Meta-learning algorithms and applications
O Bohdal - 2024 - era.ed.ac.uk
Meta-learning in the broader context concerns how an agent learns about their own
learning, allowing them to improve their learning process. Learning how to learn is not only …
learning, allowing them to improve their learning process. Learning how to learn is not only …