March 19, 2021 — Lawrence Livermore National Laboratory (LLNL) computer scientists have developed a new framework and an accompanying visualization tool that leverages deep reinforcement learning for ...

Neural architecture search is an aspect of AutoML, along with feature engineering, transfer learning, and hyperparameter optimization. It’s probably the hardest machine learning problem ...

you will see it’s a layered stack of regression functions. An academic study by Goodfellow et al. in 2014 reinvigorated the interest in deepfakes through a new deep learning architecture called ...

Depending on the deep learning architecture, data size, and task at hand, we sometimes require 1 GPU, and sometimes, several of them, a decision data scientist needs to make based on known ...

Another good example of the application of deep learning is image classification. Because living organisms process images with their visual cortex, many researchers have taken the architecture of ...

“FPGA based deep learning accelerators meet most requirements,” Yao says. “They have acceptable power and performance, they can support customized architecture and have high on-chip memory bandwidth ...