Deep Frank-Wolfe for neural network optimization
Learning a deep neural network requires solving a challenging optimization problem: it is a high-dimensional, non-convex and non-smooth minimization problem with a large number of terms. The current practice in neural network optimization is to rely on the stochastic gradient descent (SGD) algorithm...
| Hlavní autoři: | , , |
|---|---|
| Médium: | Internet publication |
| Jazyk: | English |
| Vydáno: |
arXiv
2018
|