2 papers
cs.LG2019
NeMo: a toolkit for building AI applications using Neural Modules
Oleksii Kuchaiev, Jason Li, Huyen Nguyen +11
NeMo (Neural Modules) is a Python framework-agnostic toolkit for creating AI applications through re-usability, abstraction, and composition. NeMo is built around neural modules, c…
cs.LG2019
Stochastic Gradient Methods with Layer-wise Adaptive Moments for Training of Deep Networks
Boris Ginsburg, Patrice Castonguay, Oleksii Hrinchuk +7
We propose NovoGrad, an adaptive stochastic gradient descent method with layer-wise gradient normalization and decoupled weight decay. In our experiments on neural networks for ima…